Daniel Steffens - UFMGSupervisors’ Statement As supervisors of Daniel Steffens’ doctoral work, we certify that we consider his thesis “Mechanisms of Low Back Pain” to be suitable

Daniel Steffens

MECHANISMS OF LOW BACK PAIN

Belo Horizonte

2015

Daniel Steffens

MECHANISMS OF LOW BACK PAIN

Belo Horizonte

2015

Tese apresentada ao Programa de

Pósgraduação em Ciências da

Reabilitação, da Escola de Educação

Física, Fisioterapia e Terapia Ocupacional

da Universidade Federal de Minas Gerais

como requisito à obtenção do título de

Doutor em Ciências da Reabilitação

Orientadora: Profª. Drª. Leani SM

Pereira

Co-Orientador: Prof. Dr. Chris Maher

Co-Orientadora: Profª. Drª. Jane Latimer

S817

2015

Steffens, Daniel

Mechanisms of low back pain. [manuscrito]/.Daniel Steffens – 2015.

245f., enc.: il.

Orientadora: Leani Souza Máximo Pereira

Co-orientador: Chris Maher

Co-orientadora: Jane Latimer

Tese (doutorado) – Universidade Federal de Minas Gerais, Escola de Educação Física,

Fisioterapia e Terapia Ocupacional.

1. Aptidão física - Teses. 2. Dor Lombar - Teses. 3. Incapacidade - Teses. I.

Pereira, Leani Souza Máximo. II. Maher, Chris. III. Latimer, Jale. IV. Universidade

Federal de Minas Gerais. Escola de Educação Física, Fisioterapia e Terapia

Ocupacional. V. Título.

CDU: 612.76 Ficha catalográfica elaborada pela equipe de bibliotecários da Biblioteca da Escola de Educação Física,

Fisioterapia e Terapia Ocupacional da Universidade Federal de Minas Gerais.

Supervisors’ Statement

As supervisors of Daniel Steffens’ doctoral work, we certify that we consider his thesis

“Mechanisms of Low Back Pain” to be suitable for examination.

Professor Leani de Souza Máximo Pereira

Universidade Federal de Minas Gerais Date: 01.01.2015

Professor Christopher Maher

The George Institute for Global Health Date: 01.01.2015

The University of Sydney

Professor Jane Latimer

The George Institute for Global Health Date: 01.01.2015

The University of Sydney

i

Candidate’s Statement

I, Daniel Steffens, hereby declare that this submission is my own work and that it

contains no material previously published or written by another person except where

acknowledged in the text. Nor does it contain material which has been accepted for the

award of another degree.

I, Daniel Steffens, understand that if I am awarded a higher degree for my thesis entitled

“Mechanisms of low back pain” being lodged herewith for examination, the thesis will

be lodged in the Universidade Federal de Minas Gerais and The University of Sydney

libraries and be available immediately for use. I agree that the University Librarian (or

in the case of a department, the Head of the Department) may supply a photocopy or

microform of the thesis to an individual for research or study or to a library.

Daniel Steffens

Date: 01.01.2015

ii

iii

iv

Acknowledgments

My thanks go firstly to my supervisors Prof Leani SM Pereira and Prof Chris G

Maher and my co-supervisor Prof Jane Latimer. Leani, all this could not be possible without

your persistence and dedication. Chris, you are the best supervisor I could have ever asked

for. Your competence, dedication, patience and sense of humour made this journey much

easier. You are truly an inspiration to all of us. Jane, your kindness and guidance allowed me

to always see the light at the end of the tunnel. You were a great co-supervisor for which I

have immense respect and admiration.

I would like to acknowledge my appreciation to the Universidade Federal de Minas

Gerais and The University of Sydney for establishing the Cotutelle agreement allowing me to

pursue my studies. I would also like to thank the George Institute for Global Health for

providing the modern infra-structure and support; and the Department of Physiotherapy from

the Universidade Federal de Minas Gerais for their support.

I am grateful to several people whose advice and support ensured that this thesis was

completed. I am indebted to all my co-authors, who played a major role in the construction of

each chapter of this thesis. In particular, I would like to thank Dr Mark Hancock for all his

support, dedication, mentorship, transparency and willingness to help. You are one of the

reasons I started my PhD.

To all my friends and colleagues, it is impossible to imagine these four years without

the BBQs, beers, laughs and advice. In particular, Zamba, Marcinha, Big Mike, Vinicius,

Tarci, Bruno, Tie, Patricia, Gustavo, Marina, Amabile, Saad, Aron, Matt and Richard. You

have made all the difference.

To all my family, Mum, Dad, brothers and sister, you all have contributed to this.

Mum, your unconditional support allowed me to choose my journey. Dad, I miss you and I

wish you were here to share this moment with me. Your son will finally become a Doctor.

You both were always there for me and I hope I have made you proud.

Finally, to the love of my life. Paula, thank you for your support, encouragement and

help at every single stage. This thesis is dedicated to you, the most important person in my

life.

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Publications and Presentations

Parts of the work presented in this thesis have been published and/or presented in the

following forms:

Publications

Steffens D, Maher CG, Ferreira ML, Hancock MJ, Glass T, Latimer J. Clinicians’

views on factors that trigger a sudden onset of low back pain. European Spine Journal.

2014; 23:512-519.

Steffens D, Ferreira ML, Latimer J, Ferreira PH, Koes BK, Blyth F, Li Q, Maher CG.

What triggers an episode of low back pain? A case-crossover study. Arthritis Care &

Research. 2015; 67:403-410.

Steffens D, Maher CG, Li Q, Ferreira ML, Pereira LSM, Koes BK, Latimer J. Effect of

weather on back pain: results from a case-crossover study. Arthritis Care & Research.

2014; 66:1867-1872.

Steffens D, Hancock MJ, Maher CG, Williams C, Jensen TS, Latimer J. Does magnetic

resonance imaging predict future low back pain? A systematic review. European

Journal of Pain. 2014; 18:755-765.

Steffens D, Hancock MJ, Maher CG, Latimer J, Satchell R, Ferreira ML, Ferreira PH,

Partington M, Bouvier AL. Prognosis of chronic low back pain in patients presenting to

a private community-based group exercise program. European Spine Journal. 2014; 23:

113-119.

Steffens D, Hancock MJ, Pereira LSM, Kent PM, Latimer J, Maher CG. Do magnetic

resonance imaging findings identify patients with low back pain who respond better to

particular interventions? A systematic review. Submitted for publication to European

Journal of Pain on 28th

October 2014.

Steffens D, Maher CG, Ferreira ML, Hancock MJ, Pereira LSM, Williams CM, Latimer

J. Influence of clinician characteristics and operational factors on recruitment of

participants with low back pain: an observational study. Journal of Manipulative

Physiological Therapeutics. 2014; 38:151-158.

vi

Steffens D, Ferreira ML, Maher CG, Latimer J, Koes BW, Blyth FM, Ferreira PH.

Triggers for an episode of sudden onset low back pain: study protocol. BMC

Musculoskeletal Disorders. 2012; 24:13-17.

Presentations


What triggers an episode of low back pain? Results of a Case-crossover study. XIII

International Back Pain Forum. Campos do Jordão, Brazil, 2014.

Steffens D, Maher CG, Li Q, Ferreira ML, Pereira LSM, Koes BK, Latimer J. Could the

weather trigger an episode of acute low back pain? A case cross-over study. XIII

International Back Pain Forum. Campos do Jordão, Brazil, 2014.


What triggers an episode of low back pain? Results of a case-crossover study.

Australian Pain Society, 34th

Annual Meeting. Hobart, Australia, 2014.


resonance imaging predict future low back pain? A systematic review. VIII Pain in

Europe. Florence, Italy, 2013.

Steffens D, Ferreira ML, Maher CG, Latimer J, Koes BW, Blyth FM, Ferreira PH. Does

the method of training of recruiting clinicians influence recruitment to a low back pain

case-crossover study. Primary Care Research on Back Pain - XII Odense International

Forum. Odense, Denmark, 2012.

Steffens D, Ferreira ML, Maher CG, Latimer J, Koes BW, Blyth F, Ferreira PH.

Clinician’s views on triggers for sudden onset low back pain. Primary Care Research

on Back Pain - XII Odense International Forum. Odense, Denmark, 2012.

Steffens D, Hancock MJ, Satchill R, Ferreira ML, Ferreira PH, Maher CG, Partington

M, Bouvier AL. Prognosis of patients with chronic low back pain presenting to a private

functional group exercise program. Australian Physiotherapy Association Biennial

Conference. Brisbane, Australia, 2011.

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Preface

This thesis is part of a Cotutelle Agreement between the Universidade Federal de

Minas Gerais and The University of Sydney made on 1 August 2011.

This thesis is arranged in Ten Chapters, written so that each chapter can be read

independently. The Universidade Federal de Minas Gerais and The University of Sydney

allow for published papers arising from the candidature to be included in the thesis.

Chapter One is an introduction to the thesis and provides an overview of the relevant

low back pain literature with a specific focus on aspects related to the mechanisms of back

pain.

Chapter Two is an observational study conducted to describe short- and long-term

factors that primary care clinicians consider important in triggering a sudden episode of acute

low back pain. This study is presented as published in the European Spine Journal.

Chapter Three is the protocol for the case-crossover study presented in Chapter

Four. This protocol is presented as published in BMC Musculoskeletal Disorders.

Chapter Four investigates the increase in risk of an episode of sudden onset, acute

low back pain associated with transient exposure to a range of physical (e.g manual tasks,

vigorous physical activity) and psychosocial factors (e.g. distraction/fatigue). The paper is

presented in the format required by Arthritis Care & Research where it has been accepted for

publication.

Chapter Five is a case-crossover study evaluating the influence of various weather

conditions on risk of an episode of sudden onset, acute low back pain. This study is presented

as published in Arthritis Care & Research.

Chapter Six is a systematic review investigating whether magnetic resonance

imaging findings of the lumbar spine predict future low back pain. This study is presented as

published in the European Journal of Pain.

Chapter Seven is an observational study investigating the prognosis and prognostic

factors for patients with chronic low back pain presenting to a private, community-based,

group exercise program. This study is presented as published in the European Spine Journal.

viii

Chapter Eight consists of a systematic review investigating if the presence of

magnetic resonance imaging findings at baseline identifies patients with low back pain who

respond better to particular interventions. The paper is presented in the format required by

European Journal of Pain where it was submitted for publication.

Chapter Nine is an observational study conducted to identify factors that influence

recruitment to a large observational study. The paper is presented in the format required by

Journal of Manipulative and Physiological Therapeutics where it has been accepted for

publication.

Finally, Chapter Ten consists of an overview, and discusses the clinical implications

and directions for further research.

Each chapter contains its own reference list. Appendices that were published as online

supplementary material are included at the end of the relevant chapter. Ethical approval was

obtained from the Human Research Ethics Committee of the University of Sydney for all

studies prior to commencement.

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Resumo

A dor lombar é um grande problema a nível mundial e está associada a

e levados custos socioeconômicos e de saúde para o indivíduo e para a sociedade. Nas

últimas décadas, apesar do número considerável de pesquisas sobre o tema, o avanço

na identificação de abordagens que forneçam resultados significativos no tratamento da

dor lombar ainda permanece limitado. A identificação ou a melhor compreensão dos

fatores de risco que aumentam a ocorrência da dor lombar, ou que estejam associados

com o prognóstico ou a resposta de tratamento, são cruciais para o desenvolvimento de

estratégias para sua prevenção. Os estudos desenvolvidos nesta tese focam na avaliação

dos mecanismos do desenvolvimento da dor lombar, em relação ao risco, prognóstico e a

resposta terapêutica.

Até o momento, evidências sobre as causas da dor lombar na população que

procura o atendimento em serviços de atenção primária à saúde permanecem limitadas.

Os profissionais que atuam em cuidados primários, que comumente atendem um grande

número desses pacientes, ainda não conseguem fornecer informações esclarecedoras

sobre as causas do aparecimento da dor lombar. O estudo observacional apresentado no

Capítulo Dois investigou os fatores de risco de curto e longo prazo que os profissionais

em cuidados primários acreditam ser responsáveis por desencadear um episódio súbito de

dor lombar aguda. Este estudo baseou-se nas opiniões de 103 profissionais em cuidados

de saúde primários que estavam recrutando participantes para um estudo caso-cruzado.

Os fatores de risco a curto e a longo prazo mais citados como responsáveis por

desencadear um episódio súbito de dor lombar aguda foram fatores biomecânicos

(89,3% e 54,2%, respectivamente) e características individuais, tais como episódios

anteriores de dor lombar (6,4%e 39,0%,respectivamente). Surpreendentemente, fatores

de risco psicológicos/psicossociais e genéticos não foram considerados por esses

profissionais, como importantes para desencadeamento de um episódio súbito de dor

lombar aguda, apesar da literatura atual considerar esses fatores como relevantes. Os

resultados apresentados no Capitulo 2 ajudará a informar aos profissionais de saúde do

setor primário sobre a importância de considerar esses fatores em programas de

prevenção e tratamento da dor lombar.

Uma melhor compreensão dos fatores que aumentam o risco de dor lombar é

crucial para o desenvolvimento de estratégias de prevenção. Estudos anteriores

concentraram-se em fatores de risco que não são modificáveis tais como a idade dos

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indivíduos ou, envolvem hábitos de vida a longo prazo como o tabagismo. Um estudo

caso-cruzado para investigar quais os fatores de risco físicos e psicossociais que

estavam presentes no período mais próximo para o aparecimento de um episódio súbito

de dor lombar aguda foi realizado. Os Capítulos Três e Quatro descrevem o protocolo

e os resultados encontrados no estudo, respectivamente. Um total de 999 pacientes que

apresentaram um novo episódio de dor lombar aguda foram recrutados por meio de 300

clínicas de atenção primária á saúde em Sidney, Austrália. A exposição a fatores

desencadeadores físicos e psicossociais durante as duas horas que precederam o início da

dor foi comparada com as mesmas duas horas em dois períodos controles, de 24 e 48

horas antes do surgimento da dor. A exposição à tarefas manuais envolvendo má postura

(odds ratio 8,03; intervalo de confiança de 95%: 5,46 a 11,82), manuseio de objetos

longe do corpo (odds ratio 6,20; intervalo de confiança de 95%: 2,41 a 15,94),

manuseio de pessoas ou animais vivos (odds ratio 5,8; intervalo de confiança de 95%:

2,25 a 14,98) ou manuseio de carga instável, difícil de pegar ou segurar (odds ratio 5,13;

intervalo de confiança de 95%:2,40 a 10,93), bem como distrair-se durante uma tarefa

(odds ratio 25,0; intervalo deconfiança de 95%: 3,4 a 184,5), ou estar cansado (odds

ratio 3,7; intervalo de confiança de95%: 2,2 a 6,3), aumentou significativamente as

chances do surgimento de um novo episódio de dor lombar. O consumo de bebidas

alcoólicas (odds ratio 1,5; intervalo de confiança de 95%: 0,6 a 3,7) ou a realização de

atividade sexual (odds ratio 0,7; intervalo de confiança de 95%: 0,3 a 1,8), não

aumentaram o risco no surgimento de dor lombar. Estas associações não foram

moderadas por atividade física habitual, índice de massa corporal, episódios anteriores

de dor lombar, ou depressão e ansiedade. A idade dos indivíduos moderou o risco

associado à exposição à cargas pesadas (odds ratio para pessoas com idades entre

20, 40 ou 60 anos foram de 13,6, 6,0 e 2,7, respectivamente) e de atividade sexual (odds

ratio para pessoas com idades entre 20, 40 ou 60 anos foram 0,05, 0,41 e 3,21,

respectivamente). Este foi o primeiro estudo a usar o desenho caso-cruzado para avaliar a

associação entre exposições físicas e psicossociais e o risco do surgimento de dor lombar

aguda. Os resultados apresentados podem ser usados para auxiliar no desenvolvimento de

novas abordagens de prevenção dor lombar.

Existem muitos fatores responsáveis por desencadear um episódio de dor lombar.

Muitos pacientes com dor musculoesquelética comumente relatam que seus sintomas são

influenciados pelo clima, no entanto, até o momento esta associação não foi avaliada

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para a condição musculoesquelética mais comum, que é a dor lombar. O estudo relatado

no Capítulo Cinco teve como objetivo investigar a influência de diferentes condições

climáticas no risco de desencadeamento de um episódio de dor lombar aguda. Foi

realizado um estudo caso-cruzado envolvendo 993 pacientes que apresentaram-se à

clínicas de atenção primária a saúde em Sidney, Austrália. As informações clínicas e

demográficas de todos os participantes foram obtidas a partir de uma entrevista. Os

parâmetros meteorológicos foram obtidos por meio do Instituto Australiano de

Meteorologia. Utilizou-se o método analítico em pares (regressão logística condicional)

para o estudo caso-cruzado para contrastar o clima no momento em que os participantes

notaram pela primeira vez a dor lombar (janela caso) com o tempo, ao mesmo tempo,

uma semana e um mês antes (janelas controle). A maioria dos participantes eram do sexo

masculino (54,2%), com idade média de 45,2 anos. Temperatura, umidade relativa do ar,

pressão atmosférica, direção do vento e precipitação não mostraram associação com o

início de um novo episódio de dor lombar. Velocidade do vento (odds ratio 1,17;

intervalo de confiança de 95%: 1,04 a 1,32; p = 0,01; para um aumento de 11 km/h) e

rajada de vento (odds ratio 1,14; intervalo de confiança de 95%:1,02 a 1,28; p =

0,02; para um aumento de 14 km/h) aumentaram as chances para o surgimento da

dor. A maioria dos parâmetros climáticos não foram associados com o surgimento da dor

lombar. A velocidade do vento e da rajada do vento foram associadas a um pequeno

aumento no risco do surgimento de dor lombar, porém essa variável não é considerada

como sendo clinicamente importante.

A ressonância magnética tem sido muito utilizada pelos médicos para a

identificação de patologias responsáveis pela dor lombar. No entanto, a importância dos

achados na ressonância magnética permanece controversa, a evidência é limitada e

nenhuma revisão sistemática sobre este tema foi conduzida até o presente momento.

Portanto, a revisão sistemática apresentada no Capítulo Seis investigou se os achados

de ressonância magnética da coluna lombar podem prever o aparecimento de futuros

casos de dor lombar em pessoas com e sem dor lombar presente. As buscas foram

realizadas em três bancos de dados internacionais (MEDLINE, EMBASE e CINAHL) e

12 estudos de coorte prospectivos foram encontrados. Devido à heterogeneidade dos

estudos incluídos, a condução de uma meta-análise não foi possível. Não foram

identificadas associações consistentes entre os achados na ressonância magnética e dor

ou incapacidade. Três estudos relataram associações significativas para Modic changes

tipo 1 com dor (odds ratio 6,2; intervalo de confiança de 95%: 1,9 a 20,2),

xii

degeneração discal com incapacidade em amostras com a presença de dor lombar (odds

ratio 2,2; intervalo de confiança de 95%: 1,2 a 4,0) e hérnia de disco com dor em uma

amostra mista, com e sem dor lombar (odds ratio 0,2; intervalo de confiança de 95%: não

reportado; p = 0,01). Poucos estudos investigaram se a ressonância magnética pode

prever o aparecimento de novos casos de dor lombar. Embora três resultados

estatisticamente significativos tenham sido encontrados, esses estudos apenas fornecem

evidências limitadas. Há uma clara necessidade de envidar esforços, para que futuros

estudos sejam conduzidos adequadamente nesta área.

O prognóstico da dor lombar crônica é considerado desfavorável. Uma melhor

compreensão dos fatores prognósticos para os pacientes com dor lombar crônica poderia

ajudar os profissionais de saúde a tratar e educar os pacientes em relação a essa

disfunção. O estudo prospectivo apresentado no Capítulo Sete teve como objetivo

analisar o prognóstico e os fatores prognósticos para pacientes com dor lombar

crônica que se apresentaram a uma clinica de fisioterapia privada para realização de

exercícios em grupo. Este estudo baseou-se em um coorte de 118 pacientes consecutivos

com dor lombar crônica atendidos em uma clínica de atenção primária. Análises de

regressão linear múltipla foram realizadas para investigar se uma série de variáveis

prognósticas (por exemplo, número de episódios anteriores) podem prever dor e

incapacidade em 12 meses de acompanhamento. A maioria dos pacientes (95%), foram

acompanhados no decorrer dos 12 meses. Aos 3 e 6 meses de acompanhamento dos

pacientes, a intensidade da dor, o incômodo causado pela dor, incapacidade e função

apresentaram melhoras semelhantes. No entanto, de 6 a 12 meses, a incapacidade e a

função continuaram a melhorar, enquanto um progresso marginal foi observado no

incômodo causado pela dor e na intensidade da dor. Os modelos finais mostraram

evidências de uma associação entre a intensidade da dor avaliada na linha de base com

a intensidade da dor aos 12 meses; enquanto que a duração do episódio atual,

incapacidade avaliada na linha de base e nível educacional foram associados com a

incapacidade aos 12 meses. A maior parte da variância no resultado não foi explicada

pelos preditores investigados neste estudo. Nossos resultados sugerem que, na população

estudada, a previsão dos resultados aos 12 meses pode ser mais difícil, ou outros

preditores não investigados devam ser considerados.

Nos últimos anos, pouco ou nenhum progresso ocorreu na identificação de

estratégias de intervenção eficazes para a dor lombar. Este fato pode ser explicado pela

dificuldade na identificação de uma causa específica de dor lombar na maioria das

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pessoas. Como resultado, uma única intervenção é oferecida para distintos grupos de

pacientes com causas de dor potencialmente diferentes. A ressonância magnética tem a

capacidade de revelar uma série de degenerações e outras anormalidades anatômicas que

acometem a coluna lombo-sacra. No entanto, pouco tem-se focado na identificação de

subgrupos baseados em possíveis causas patoanatômicas da dor lombar. Assim, a revisão

sistemática apresentada no Capítulo Oito investigou se a presença de achados de

ressonância magnética tem a capacidade de identificar pacientes com dor lombar que

respondem melhor a certas intervenções terapeuticas. Esta revisão conduziu buscas em

três bancos de dados (MEDLINE, EMBASE e CENTRAL) e incluiu ensaios clínicos

randomizados que investigaram achados na ressonância magnética como modificadores

do efeito de tratamento para pacientes com dor lombar ou ciática. Baseado nos resultados

de oito estudos que investigaram interações em 38 subgrupos para combinações de

diferentes achados de ressonância magnética, intervenções e resultados, apenas dois

subgrupos apresentaram uma interação significativa. Atualmente, existe uma

carência de estudos para determinar se os achados de uma ressonância magnética

podem modificar o efeito do tratamento para dor lombar ou ciática.

A dificuldade de recrutamento dos pacientes para participar em pesquisas na

atenção primária á saúde é um fator importante que impede a realização de estudos

contendo um adequado e representativo tamanho amostral. Há uma carência de estudos

que investigam quais seriam as barreiras e facilitadores para aumentar o recrutamento de

pacientes pelos profissionais para participar de estudos observacionais em cuidados

primários à saúde. O estudo final desta tese é apresentado no Capítulo Nove e teve como

objetivo investigar os fatores associados ao recrutamento de participantes para um estudo

observacional. O estudo incluiu uma amostra de 138 profissionais em cuidados

primários que identificaram 1.585 pacientes de outubro de 2011 a novembro de 2012.

Os dados foram analisados através de uma regressão binomial negativa multivariada para

determinar as associações de uma variedade de características clínicas e fatores

operacionais, como a taxa de recrutamento. Os profissionais em cuidados primários

recrutaram 951 participantes, a uma taxa de 0,99 participantes por mês. Dois fatores

operacionais (profissionais que escolheram receber treinamento pelo telefone e o número

de pacientes não elegíveis referidos ao estudo) e um fator de clínico (profissionais que

não eram membros de sua respectiva associação) foram associados com a taxa de

recrutamento. O tamanho amostral necessário para o estudo foi atingido dentro de um

prazo razoável. No entanto, os fatores operacionais e clínicos associados à taxa de

xiv

recrutamento parecem limitados.

Os estudos apresentados nesta tese contribuem para a melhor compreensão dos

mecanismos responsáveis pela dor lombar. Foi constatado que fatores de risco

biomecânicos e individuais foram considerados pelos profissionais em cuidados primários

como sendo fatores importantes para o desenvolvimento de dor lombar aguda e devem ser

investigados em estudos futuros. A exposição a uma variedade de fatores físicos e

psicossociais aumentou o risco de um episódio de dor lombar aguda e devem ser

considerados. Parâmetros meteorológicos têm pouco efeito no surgimento de um episódio

de dor lombar aguda. Apesar de a velocidade do vento e de rajadas de vento mostrarem ter

um efeito pequeno, a magnitude do aumento não foi clinicamente relevante. Esses

resultados contribuem para o conhecimento sobre os fatores de risco da dor lombar e

podem orientar futuras estratégias de prevenção. Poucos estudos investigaram a associação

entre os achados da ressonância magnética e dor lombar, portanto, futuros estudos nesta

área se fazem necessários. O prognóstico de pacientes com dor lombar crônica que se

apresentaram a uma clínica de fisioterapia privada para realização de exercícios em grupo

é favorável. Esta informação é importante tanto para profissionais da área da saúde quanto

para pacientes, uma vez que contribui para uma expectativa realista, podendo ser usado

para orientar a tomada de decisões sobre a necessidade de implementação de intervenções

adicionais. Além disso, a necessidade de estudos de alta qualidade, com tamanho amostral

adequados, investigando achados da ressonância magnética como modificadores de efeito

de tratamento é essencial para determinar a importância clínica destes resultados na dor

lombar e ciática. Finalmente, esta tese fornece evidências de que é possível recrutar um

grande número de participantes para estudos observacionais. No entanto, a identificação de

fatores que possam estimular o recrutamento ainda permanece obscura.

Palavras-chave: Dor Lombar. Fatores de Risco. Mecanismo. Incapacidade. Ressonância

Magnética.

xv

Abstract

Low back pain is a very common condition that presents a significant burden to

individuals and society, being one of the leading causes of disability globally. Despite

considerable research over the past decades, there has been limited progress in identifying

management approaches that provide large treatment effects. Progress in identifying effective

prevention strategies has been no better. The identification, or better understanding, of factors

that increase the risk for the development of back pain, or that are associated with prognosis

or response to treatment, is crucial for developing and refining prevention and management

strategies. The studies in this thesis focus on evaluating the mechanisms of low back pain in

relation to risk, prognosis and response to treatment.

There is limited information about the causes of low back pain in the general

population presenting to care. Primary care clinicians who commonly manage a large number

of these patients could provide valuable insights into what may be the most important causes

for low back pain. The observational study presented in Chapter Two investigated the short-

and long-term risk factors that primary care clinicians believe most likely to trigger a sudden

episode of acute low back pain. This study was based on the views of 103 primary care

clinicians recruiting patients for a large case-crossover study. The most endorsed short- and

long-term risk factors to trigger an episode of sudden acute low back pain were

biomechanical (89.3% and 54.2%, respectively) and traits of the individual such as previous

low back pain episodes (6.4% and 39.0%, respectively). Surprisingly,

psychological/psychosocial and genetic risk factors were not considered important risk

factors for an episode of low back pain. Primary care clinicians believe that biomechanical

and individual risk factors are the most important factors to trigger an episode of low back

pain. The reason why the current literature considers psychosocial and genetic risk factors

important and primary care clinicians do not should be further investigated. This information

will help inform low back pain management and prevention programs.

A better understanding of what factors increase the risk of back pain is crucial to the

development of prevention strategies. Previous studies have focused on factors that are either

not modifiable (e.g. age) or involve long-term exposure (e.g. smoking). To evaluate factors

more proximal to the pain onset, a case-crossover study investigating a range of physical and

psychosocial risk factors for an episode of sudden onset, acute back pain was conducted.

Chapter Three and Four describe the study protocol and the report of the study,

xvi

respectively. A total of 999 patients with a new episode of acute low back pain were recruited

from 300 primary care clinics in Sydney. Exposure to physical and psychosocial triggers

during the two hours preceding back pain onset was compared to that in the 2-hour periods 24

and 48 hours before the onset. Exposure to manual tasks involving awkward positioning

(odds ratio 8.03; 95% confidence interval 5.46 to 11.82), objects far from the body (odds

ratio 6.20; 95% confidence interval 2.41 to 15.94), handling of live people or animals (odds

ratio 5.8; 95% confidence interval 2.25 to 14.98) or a load that was unstable, unbalanced or

difficult to grasp or hold (odds ratio 5.13; 95% confidence interval 2.40 to 10.93); as well as

being distracted during a task (odds ratio 25.0; 95% confidence interval 3.4 to 184.5), or

being fatigued (odds ratio 3.7; 95% confidence interval 2.2 to 6.3) significantly increased the

odds of a new episode of back pain. Exposure to alcohol consumption (odds ratio 1.5; 95%

confidence interval 0.6 to 3.7) or sexual activity (odds ratio 0.7; 95% confidence interval 0.3

to 1.8) did not increase risk of back pain onset. These associations were not moderated by

habitual physical activity, body mass index, previous low back pain episodes, or depression

and anxiety. Age moderated the risk associated with exposure to heavy loads (odds ratios for

people aged 20, 40 or 60 years were 13.6, 6.0 and 2.7 respectively) and sexual activity (odds

ratios for people aged 20, 40 or 60 years were 0.05, 0.41 and 3.21 respectively). This is the

first study to use this robust design to evaluate the association of physical and psychosocial

exposures and low back pain onset. These results can inform the development of new

prevention approaches for back pain.

There are many factors believed to trigger an episode of low back pain. Many patients

with musculoskeletal pain commonly report that their symptoms are influenced by the

weather, but this issue has not been evaluated for the most common musculoskeletal

condition, back pain. The study reported in Chapter Five aimed to investigate the influence

of various weather conditions on risk of acute low back pain. A case-crossover study was

performed with 993 patients presenting to primary care in Sydney. All participants’

demographic and clinical information were obtained from an interview. Weather parameters

were obtained from the Australian Bureau of Meteorology. We used the pair-matched

analytic approach (conditional logistic regression) for the case-crossover design to contrast

the weather at the time when participants first noticed their back pain (case window) with the

weather at the same time one week and one month prior (control windows). Most participants

were male (54.2%), with mean age of 45.2 years. Temperature, relative humidity, air

pressure, wind direction and precipitation showed no association with onset of a new episode

xvii

of back pain. Higher wind speed (odds ratio 1.17; 95% CI 1.04 to 1.32; p=0.01; for an

increase of 11 km/h) and wind gust (odds ratio 1.14; 95% CI 1.02 to 1.28; p=0.02; for an

increase of 14 km/h) increased the odds of pain onset. Most weather parameters were not

associated with the onset of back pain. Higher wind speed and wind gust speed provided a

very small increase in risk of back pain onset that does not seem clinically important.

Magnetic resonance imaging has been increasingly used by clinicians in order to

identify pathology responsible for low back pain. However, the importance of findings on

magnetic resonance imaging remains controversial, the evidence is limited and no systematic

review on this topic has been conducted. Therefore, the systematic review presented in

Chapter Six investigated whether magnetic resonance imaging findings of the lumbar spine

predict future low back pain in different samples with and without low back pain. Searches

performed in three international databases (MEDLINE, EMBASE and CINAHL) located 12

prospective cohort studies. Due to heterogeneity of the included studies, pooling the data for

a meta-analysis was not possible. No consistent associations between findings on magnetic

resonance imaging and pain or disability were identified. Three studies reported significant

associations for Modic changes type 1 with pain (odds ratio 6.2; 95% confidence interval 1.9

to 20.2), disc degeneration with disability in samples with current LBP (odds ratio 2.2; 95%

confidence interval 1.2 to 4.0) and disc herniation with pain in a mixed sample (odds ratio

0.2; 95% confidence interval not provided; p = 0.01). Few studies have investigated if

magnetic resonance imaging findings predict future low back pain. Although there were three

statistically significant results, overall these studies only provide limited evidence. There is a

clear need for further appropriately designed research.

The prognosis for chronic low back pain is considered poor. Better understanding of

prognostic factors for patients with chronic low back pain may help clinicians to manage and

educate patients regarding their future health. The prospective study presented in Chapter

Seven aimed to examine the prognosis and prognostic factors for patients with chronic low

back pain who presented to a private, community-based, group exercise program. This study

was based on the data of a cohort of 118 consecutive patients with chronic low back pain in a

primary care setting. Multivariate linear regression analyses were performed to investigate

whether a range of prognostic variables (e.g. number of previous episodes) predict pain and

disability at 12 months follow up. Most of the patients (95%) were followed up at 12 months.

At 3 and 6 months, pain intensity, bothersomeness, disability and function improved

similarly, but from 6 to 12 months, disability and function continued to improve while only

xviii

small further changes in bothersomeness and pain intensity occurred. The final models

showed evidence of an association between baseline pain intensity and 12 months pain

outcomes; whereas duration of current episode, baseline disability and educational level

accounted for 12 months disability outcome. Most of the variance in outcome was not

explained by any of the predictors we investigated in this study. Our findings suggest that in

this population, predicting 12 month outcome may be more difficult or other predictors may

be more important.

There has been little or no progress in identifying effective intervention strategies for

low back pain. This lack of progress may be explained by the current inability to identify a

specific cause in most people. As a result, a single intervention is provided to heterogeneous

groups of patients with potentially different causes of their pain. Magnetic resonance imaging

can reveal a range of degenerative findings and anatomical abnormalities affecting the

lumbosacral spine. However, very little attention has focussed on identifying subgroups

based on possible patho-anatomical causes of low back pain. Thus, the systematic review

presented in Chapter Eight investigated if the presence of magnetic resonance imaging

findings identifies patients with low back pain who respond better to particular interventions.

This review conducted a sensitive search in three databases (MEDLINE, EMBASE and

CENTRAL) and included randomised controlled trials investigating findings on magnetic

resonance imaging as treatment effect modifiers for patients with low back pain or sciatica.

Based on data from eight published reports investigating 38 subgroup interactions for

combinations of different magnetic resonance imaging findings, interventions and outcomes,

two subgroups displayed a significant interaction. At present, there is a lack of studies to

determine whether magnetic resonance imaging features modify effect of treatment for low

back pain or sciatica.

Patient recruitment to research studies is often difficult. Problematic recruitment in

primary care is one major factor preventing the collection of large representative samples for

research. Studies investigating factors that enhance recruitment to observational studies in

primary care is lacking. The final study of this thesis is presented in Chapter Nine and aimed

to investigate factors associated with recruitment of participants to an observational study.

The study included a sample of 138 primary care clinicians that screened 1,585 patients from

October 2011 to November 2012. Multivariate negative binomial regression was used to

determine associations of a variety of clinician characteristics and operational factors with the

recruitment rate. Primary care clinicians recruited 951 participants at a rate of 0.99

xix

participants per month. Two operational factors (clinicians who chose to be trained by

telephone and number of ineligible patients referred) and one clinician factor (clinicians who

were not member of their association) were associated with recruitment rate. We reached our

target sample size in a reasonable time frame. However, the operational and clinician factors

associated with recruitment rate seem limited.

Overall, the studies described in this thesis have provided an important contribution to

better understanding the mechanisms of back pain. Firstly, biomechanical and individual risk

factors were considered by primary care clinicians’ to be important triggers for acute low

back pain and should be investigated further in future research. Secondly, exposure to a range

of physical and psychosocial triggers increased the risk of an acute low back pain episode.

Weather parameters have little effect on triggering an episode of acute low back pain. While

wind speed and wind gusts were shown to have a small effect the magnitude of the increase

was not clinically relevant. These results are important in increasing our knowledge about

risk factors for low back pain and guide future prevention strategies. A systematic review of

the literature found only a few studies on the association between findings of magnetic

resonance imaging and low back pain, and clearly more studies in this area are needed.

Thirdly, the prognosis of patients with chronic low back pain presenting to a private,

community-based, group exercise program is favourable. This information is important for

clinicians and patients as it helps with realistic expectation and can be used to guide decision

making regarding the need for additional interventions. In addition, the need for high quality,

adequately powered trials investigating magnetic resonance imaging findings as effect

modifiers is essential to determine the clinical importance of these findings in low back pain

and sciatica. Finally, this thesis provides evidence that it is reasonably easy to recruit large

number of participants to observational studies; however, the identification of consistent

factors that increase recruitment remains unclear.

Keywords: Low back pain. Risk Factors. Mechanism. Disability. Magnetic Resonance

Imaging.

xx

Table of Contents

Supervisors’ statement ................................................................................................................ i

Candidate’s statement ................................................................................................................ ii

Approval letter .......................................................................................................................... iii

Record ....................................................................................................................................... iv

Acknowledgements .................................................................................................................... v

Publications and presentations .................................................................................................. vi

Preface ..................................................................................................................................... viii

Abstract ...................................................................................................................................... x

Resumo (Abstract in Portuguese) ........................................................................................... xvi

Chapter One: Introduction ..................................................................................................... 26

1. Epidemiology of low back pain .................................................................................... 27

2. Economic burden of low back pain .............................................................................. 27

3. Definition and classification of low back pain ............................................................. 28

4. Mechanisms of low back pain ...................................................................................... 29

4.1 Risk factors .......................................................................................................... 29

4.1.1. Primary care clinician’s perception on risk factors for low back pain .. 30

4.1.2. Physical and psychosocial risk factors ................................................... 30

4.1.3. Environmental factors and low back pain .............................................. 31

4.1.4. Magnetic resonance imaging ................................................................. 32

4.2. Prognostic factors.................................................................................................. 32

4.2.1. Prognostic factors for chronic low back pain ........................................ 33

4.3. Subgroup of low back pain ................................................................................... 33

4.3.1. Magnetic resonance imaging subgrouping ............................................ 34

5. Recruitment for large observational studies of low back pain ...................................... 35

5.1. Factors that influence recruitment to observational studies .................................. 35

6. Aims of the thesis ......................................................................................................... 36

xxi

7. References ..................................................................................................................... 37

Chapter Two: Clinicians’ views on factors that trigger a sudden onset of low back pain ..... 46

Statement of authorship contribution ................................................................................ 47

Abstract ............................................................................................................................. 48

Introduction ....................................................................................................................... 48

Materials and methods ...................................................................................................... 49

Results ............................................................................................................................... 51

Discussion ......................................................................................................................... 52

Conclusions ....................................................................................................................... 53

References ......................................................................................................................... 53

Chapter Three: Triggers for an episode of sudden onset low back pain: study protocol ..... 56


Abstract ............................................................................................................................. 58

Background ....................................................................................................................... 58

Methods/Design ................................................................................................................ 59

Discussion ......................................................................................................................... 61

References ......................................................................................................................... 61

Additional file 1: Clinicians’ questionnaire ...................................................................... 63

Additional file 2: Study participants’ questionnaire ......................................................... 64

Chapter Four: What triggers an episode of acute low back pain? A case-crossover study . 79


Abstract ............................................................................................................................. 81

Introduction ....................................................................................................................... 81

Patients and methods ........................................................................................................ 81

Results ............................................................................................................................... 83

Discussion ......................................................................................................................... 86

References ......................................................................................................................... 88

xxii

Appendix Table 1 .............................................................................................................. 89

Appendix Table 2 .............................................................................................................. 91

Appendix Table 3 .............................................................................................................. 93

Appendix Table 4 .............................................................................................................. 95

Appendix 5 ........................................................................................................................ 97

Chapter Five: Effect of weather on back pain: Results from a case-crossover study ......... 112

Statement of authorship contribution .............................................................................. 113

Abstract ........................................................................................................................... 114

Introduction ..................................................................................................................... 114

Subjects and methods ...................................................................................................... 115

Results ............................................................................................................................. 116

Discussion ....................................................................................................................... 116

References ....................................................................................................................... 119

Chapter Six: Does magnetic resonance imaging predict future low back pain? A systematic

review ..................................................................................................................................... 120


Abstract ........................................................................................................................... 122

Introduction ..................................................................................................................... 122

Methods .......................................................................................................................... 123

Results ............................................................................................................................. 124

Discussion ....................................................................................................................... 130

Conclusions ..................................................................................................................... 131

References ....................................................................................................................... 131

Appendix S1 ................................................................................................................... 133

Appendix S2 ................................................................................................................... 134

Chapter Seven: Prognosis of chronic low back pain in patients presenting to a private

community-based group exercise program ............................................................................ 136


xxiii

Abstract ........................................................................................................................... 138

Introduction ..................................................................................................................... 138

Material and methods ...................................................................................................... 139

Results ............................................................................................................................. 140

Discussion ....................................................................................................................... 141

Conclusions ..................................................................................................................... 142

References ....................................................................................................................... 144

Chapter Eight: Do magnetic resonance imaging findings identify patients with low back

pain who respond better to particular interventions? A systematic review ........................... 145


Abstract ........................................................................................................................... 148

Introduction ..................................................................................................................... 149

Methods .......................................................................................................................... 151

Results ............................................................................................................................. 154

Discussion ....................................................................................................................... 159

Conclusions ..................................................................................................................... 162

References ....................................................................................................................... 163

Figure 1 ........................................................................................................................... 168

Table 1 ............................................................................................................................ 169

Table 2 ............................................................................................................................ 170

Table 3 ............................................................................................................................ 172

Appendix S1 ................................................................................................................... 175

Appendix S2 ................................................................................................................... 176

Appendix S3 ................................................................................................................... 177

Appendix S4 ................................................................................................................... 179

Chapter Nine: Clinician characteristics and operational factors have limited influence on

participant recruitment in primary care: Results from an observational study ...................... 183


xxiv

Abstract ........................................................................................................................... 185

Introduction ..................................................................................................................... 185

Methods .......................................................................................................................... 186

Results ............................................................................................................................. 188

Discussion ....................................................................................................................... 189

Conclusion ...................................................................................................................... 191

References ....................................................................................................................... 191

Chapter Ten: Conclusions .................................................................................................... 193

10.1. Aim ........................................................................................................................ 194

10.2. Overview of principal findings .............................................................................. 195

10.3. Implications and suggestions for future research .................................................. 196

10.3.1. Mechanism: Risk factors for low back pain .................................................. 196

10.3.2. Management: Prognosis and subgroups for low back pain ........................... 199

10.3.3. Factors influencing recruitment rate .............................................................. 200

10.4. References .............................................................................................................. 202

Appendix ............................................................................................................................... 205

Appendix A: Media coverage of Chapter Five ............................................................... 206

Appendix B: Curriculum Vitae ....................................................................................... 237

xxv

Chapter One

Introduction

26

1. Epidemiology of low back pain

Low back pain is an extremely common health problem that affects a large part of the

population during their lifetime (HOY et al., 2010; HOY et al., 2012). Until 10 years ago, it

was largely thought of as a problem of developed Western countries (VOLINN, 1997).

However, since that time an increasing number of studies have demonstrated that low back

pain is also a major problem in less developed countries (MARIETTE and MARIETTE,

2003; LOUW, MORRIS and GRIMMER-SOMERS, 2007; HOY, BROOKS et al., 2010;

BALAGUE et al., 2012). It is estimated that over one year, the incidence of people who have

a first-ever episode of low back pain ranged from 6.3% to 15.4%, and the one year incidence

of people who have any episode of low back pain (i.e., first-ever or recurrent) ranged from

1.5% to 36% (HOY, BROOKS et al., 2010). The highest prevalence of low back pain is

among females and people aged 40 to 80 years. The mean (SD) global prevalence of activity

limiting low back pain lasting for more than 1 day is estimated to be 11.9% (2.0) (HOY,

BAIN et al., 2012). Although low back pain is not a life threatening condition, it is the

leading cause of activity limitation and work absence throughout much of the world, and it

causes an enormous economic burden on individuals, families, communities, industry and

governments (THELIN, HOLMBERG and THELIN, 2008; FERREIRA et al., 2011;

MURRAY et al., 2012).

2. Economic burden of low back pain

The economic burden of low back pain is very large and appears to be rising. It is

estimated that the number of visits to allied health professionals exceeds 30 million per year

in the United States alone (ANDERSSON, 1999). This high frequency of annual visits leads

to both high direct and indirect costs (HOY et al., 2010). Direct costs includes resources

spent on assessing and treating low back pain, such as medications, assistive devices,

diagnostic tests, and may also include non-medical costs incurred by the patient and family

and other public resources (e.g. transportation). Indirect costs commonly include costs related

to employment and household productivity (EKMAN, JOHNELL and LIDGREN, 2005;

DAGENAIS, CARO and HALDEMAN, 2008).

In the United States, the economic burden for low back pain is estimated to be over

US$85 billion a year (DAGENAIS, CARO and HALDEMAN, 2008). In Australia AU$ 9.17

27

billion per annum is the total cost spent on care for low back pain (WALKER, MULLER and

GRANT, 2003). The total annual cost in Europe has been estimated, for instance, €6.4 billion

in the Netherlands (LAMBEEK et al., 2011), €6.6 billion in Switzerland (WIESER et al.,

2011), ₤12.3 billion in the United Kingdom (HOY, BROOKS et al., 2010) and €1.9 billion in

Sweden (EKMAN, JOHNELL and LIDGREN, 2005). Although the economic burden for low

back varies among countries, it is apparent that low back pain represents an enormous public

health problem worldwide.

3. Definition and classification of low back pain

Low back pain is defined as pain and discomfort, localised below the costal margin

and above the inferior gluteal folds, with or without leg pain (VAN TULDER et al., 2006).

Diagnostic triage is a simple and practical classification, which has gained international

acceptance, by dividing low back pain into three main categories: (i) serious spinal

pathologies; (ii) Nerve root pain (radicular pain)/spinal canal stenosis; and (iii) non-specific

low back pain (KOES et al., 2010).

Serious spinal pathologies include spinal tumours, vertebral infections, cauda equina

syndrome, vertebral fracture and inflammatory diseases such as ankylosing spondylitis

(CHOU et al., 2007). Only a minority of patients (less than 1%) with acute low back pain

presenting to primary care are diagnosed with a serious spinal pathology (HENSCHKE et al.,

2009). When serious spinal pathology is suspected as a cause of low back pain, further

diagnostic investigations are usually required. Guidelines recommend the use of red flags to

screen for serious pathology and to identify those patients that may need imaging and

laboratory test or specialist referral to establish a definitive diagnosis (MAHER et al., 2011).

Nerve root pain (radicular pain) or spinal canal stenosis represent approximately 5%

of the low back pain cases and are characterised by presentations where leg pain is dominant

(KONSTANTINOU and DUNN, 2008). In approximately 90% of the case of leg dominant

pain the condition is caused by a herniated disc with nerve root compression, but lumbar

canal or foraminal stenosis and (less often) tumours or cysts are other possible causes

(VALAT et al., 2010). While there are a range of definitions of sciatica, the key clinical

features that can help clinicians to distinguish it from nonspecific low back pain include

unilateral leg pain that is worse than the low back pain, pain radiating below the knee,

28

presence of numbness or pins and needles in a dermatomal distribution, positive results on a

straight leg raise test, and weakness or reflex changes, or both, in a myotomal distribution

(KOES, VAN TULDER and PEUL, 2007).

Non-specific low back pain is a term used synonymously with simple low back pain

or mechanical low back pain and is defined as low back pain not attributable to a

recognisable, known specific pathology (BALAGUE, MANNION et al., 2012). Due to the

inability to identify the source of pain, the vast majority of low back pain patients

(approximately 90%) fall into the non-specific low back pain category (HANCOCK et al.,

2007).

Low back pain is often classified in three stages (acute, sub-acute and chronic)

according to its duration and this provides some information to the clinician with regards to

treatment and prognosis. Acute low back pain is usually defined as an episode persisting for

less than 6 weeks; sub-acute low back pain as low back pain persisting between 6 to 12

weeks and chronic low back pain as low back pain persisting for 12 weeks or longer (VAN

TULDER, BECKER et al., 2006).

4. Mechanisms of low back pain

Low back pain may originate from many anatomical structures in the lumbar spine,

including bones, intervertebral discs, ligaments, muscles, neural structures and blood vessels

(DEYO and WEINSTEIN, 2001). However, the exact source of low back pain is often

difficult to identify using conventional tests available in primary care (ANDERSSON, 1999;

HANCOCK, MAHER et al., 2007). Research into risk factors for low back pain is often

challenging due to heterogeneity across research methods, case definitions and study

populations, it is clear that there are a number of environmental and individual factors that

influence the onset and course of low back pain (HOY, BROOKS et al., 2010).

4.1. Risk factors

Low back pain is a complex condition with many factors believed to contribute to its

onset (LATZA et al., 2000). Investigations into risk factors for low back pain is in a

developing stage when compared with other common conditions, such as cardiovascular

29

disease and cancer (MANEK and MACGREGOR, 2005). Broadly, the risk factors associated

with low back pain can be classified as individual, psychosocial, occupational, genetic and

biomechanical (HAMBERG-VAN REENEN et al., 2007; LANG et al., 2012; TAYLOR et

al., 2014). There are a reasonable number of recognised risk factors for low back pain,

however, most of these risk factors are not robust or replicable, and many are not modifiable

(TAYLOR, GOODE et al., 2014). Identifying factors that may increase the risk for or

predispose individuals to the development of back pain is critical in attempting to reduce the

prevalence and ultimately the social impact of this condition (RUBIN, 2007).

4.1.1. Primary care clinician’s perceptions on risk factors for low back pain

Risk factors for the development of low back pain in the general population who

present to primary health clinics are poorly understood (VAN TULDER, BECKER et al.,

2006), despite the high volume of patients seeking care (DEYO and PHILLIPS, 1996). One

reason for this is that most work up-to-date has focused on samples of specific occupational

groups or working conditions (BURDORF, NAAKTGEBOREN and DE GROOT, 1993;

MURTEZANI et al., 2011; FERGUSON et al., 2012; VANDERGRIFT et al., 2012).

Although studies conducted in occupational settings may reveal important risk factors for

work-related back pain, these risks may not be relevant to other populations, such as those

drawn from primary care. Primary care clinicians who frequently manage patients with low

back pain may provide an important understanding into the most common risk factors. The

identification of putative risk factors in primary care is essential to strengthen future research

and help inform low back pain prevention programs. Chapter Two presents the most likely

risk factors involving short and long-term exposure that primary care clinicians believe could

trigger a sudden episode of acute low back pain.

4.1.2. Physical and psychosocial risk factors

Many studies have attempted to identify and evaluate the contribution of multiple

different demographic, physical, socioeconomic, psychological, and occupational factors to

the development of back pain (VINDIGNI et al., 2005; RUBIN, 2007; TAYLOR, GOODE et

al., 2014). Known non-modifiable risk factors for low back pain include increasing age,

number of children, previous episode of low back pain and major scoliosis. Those that are

30

modifiable are poor health, obesity, smoking and prolonged sitting (VINDIGNI, WALKER et

al., 2005). However, there is a significant limitation in interpreting the literature on risk

factors for low back pain. Most of the recognised risk factors were assessed only in single or

small studies, with weak and non-reproducible evidence to support a definite association, are

not robust or replicable across studies, and were not modifiable (HURWITZ and

MORGENSTERN, 1997; KOPEC, SAYRE and ESDAILE, 2004; RUBIN, 2007; TAYLOR,

GOODE et al., 2014). Another problem with previous studies on risk factors for low back

pain is the focus on long-term exposure. Little is known about short-term exposure to

physical and psychological risk e.g. distraction while lifting. Modifying such risk factors may

be extremely important in preventing back pain recurrence.

One of the best designs to investigate transient risk factors is the case-crossover

design. This design is more efficient than cohort designs because it samples only cases and

may be less exposed to selection bias than case-control designs because cases provide their

own control data (MACLURE, 1991). One of the main advantages of the case-crossover

design is that each case serves as its own control. Consequently, case-crossover studies are

not confounded by time-invariant risk factors. Another advantage is that the case-crossover

design is immune to one of the main causes of bias in case-control studies: the selection of

control that is not representative of the population that produced the cases. A further

advantage is the ability to assess short-term reversible exposures (MACLURE, 1991;

MACLURE and MITTLEMAN, 2000). Chapter Three represents the published study

protocol of a case-crossover study investigating the association between an episode of sudden

onset, acute back pain with transient exposure to a range of physical and psychosocial factors.

The results of this study are described in Chapter Four.

4.1.3. Environmental factors and low back pain

There are an increasing number of studies examining the association between

environmental factors (e.g. temperature, humidity, air pressure, wind and precipitation) and

the onset of musculoskeletal conditions. Most of the efforts to measure climatic effects have

been directed at individuals with rheumatoid arthritis and chronic pain (JAMISON,

ANDERSON and SLATER, 1995; PATBERG and RASKER, 2004; ABASOLO et al.,

2013). Patients with musculoskeletal pain (e.g. low back pain) commonly report that certain

weather conditions influence their symptoms (SMEDSLUND et al., 2009). Despite the high

31

frequency with which this belief is reported, there are few robust studies that have

investigated this potential association (TENIAS et al., 2009; ABASOLO, TOBIAS et al.,

2013). Chapter Five investigates the influence of various weather conditions on risk of low

back pain.

4.1.4. Magnetic resonance imaging

Most low back pain sufferers, around 90%, are classified as having non-specific low

back pain (VAN TULDER, BECKER et al., 2006), reflecting the inability to identify a clear

anatomical source for the pain (WANG, VIDEMAN and BATTIE, 2012). If the source of

pain could be identified in at least some of these patients, then it is possible that more logical

and effective interventions could be found (HANCOCK, MAHER et al., 2007).

Magnetic resonance imaging is the preferred investigation for most spinal diseases

and is increasingly requested for people with low back pain (SHEEHAN, 2010). Various

abnormalities can be identified on lumbar magnetic resonance imaging, including disc

herniation, nerve root impingement, disc degeneration, and high intensity zone or annular tear

(ENDEAN, PALMER and COGGON, 2011). However, the importance of findings on

magnetic resonance imaging remains controversial (WASSENAAR et al., 2012). Many

studies have documented a high prevalence of disc abnormalities on imaging in

asymptomatic subjects (JARVIK et al., 2001). Magnetic resonance imaging findings in

currently asymptomatic people may represent markers of early pre-symptomatic disease that

is later characterized by episodes of pain and/or disability. Chapter Six reports on a

systematic review that sought to investigate whether magnetic resonance imaging findings of

the lumbar spine predict future low back pain in different samples with and without low back

pain.

4.2. Prognostic factors

Prognosis is a description of the course or prediction of the outcome of a health

condition over time (HAYDEN et al., 2010). Important to prognosis is consideration and

assessment of characteristics or factors that are associated with or determine the course of a

condition. Clinicians may use prognostic information to educate or inform the management

32

of their patients (CROFT, DUNN and RASPE, 2006). The likely prognosis of low back pain

varies according to the duration of symptoms. The prognosis for acute low back pain is

inconsistently reported, with estimates of recovery ranging from 39% to 90% (KOES, VAN

TULDER et al., 2010; DA et al., 2012). Patients presenting with a longer duration with low

back pain or with recurrent low back pain the prognosis may be less favourable (KOES, VAN

TULDER et al., 2010).

4.2.1. Prognostic factors for chronic low back pain

For those patients with symptoms persisting for longer than 3 months, approximately

one third will recover within 1-2 years after initial onset (VON KORFF et al., 1993; COSTA

LDA et al., 2009). According to a recent systematic review, the prognosis of patients

suffering from chronic pain is less favourable for those who have taken previous sick leave

for low back pain, have high disability levels or high pain intensity at onset of chronic low

back pain, have lower education, perceive themselves as having a high risk of persistent pain,

and were born outside Australia (COSTA LDA, MAHER et al., 2009). Patients presenting

for care in settings where these adverse prognostic factors are uncommon may have a more

favourable prognosis than widely reported. Until now no study has investigated the prognosis

of people with chronic low back pain attending a private, community-based, group exercise

program. Chapter Seven reports the prognosis and prognostic factors for this population.

4.3. Subgroups of low back pain

To date, there are clear trends in recent high quality randomised clinical trials, that

show that the sorts of interventions that primary care clinicians have to offer, on average,

have small (sometimes insignificant) to moderate effects (LITTLE et al., 2008; LAMB et al.,

2010), and often there is little or no difference between the effectiveness of different

interventions (CAIRNS, FOSTER and WRIGHT, 2006; JOHNSON et al., 2007). One

explanation for this lack of progress may be that a single intervention is usually provided to

heterogeneous groups of patients with potentially different causes of their pain. Many

clinicians and researchers believe that there are subgroups of people with spinal pain who

respond differently to treatment and have different prognosis (KENT, KEATING and

BUCHBINDER, 2009). The Identification of subgroups of low back pain patients has been

33

identified as a key research priority in the field (COSTA LDA et al., 2013), which may lead

to improve low back pain patient’s outcome.

Two recent reviews have investigated subgrouping of low back pain treatment. Most

previous research in this area has focussed on identifying clinical and psychosocial variables

associated with patients who respond better to different interventions (KENT, MJOSUND

and PETERSEN, 2010; KENT and KJAER, 2012). However, very little attention has

focussed on identifying subgroups based on possible patho-anatomical causes of low back

pain.

4.3.1. Magnetic resonance imaging subgrouping

There has been considerable interest in magnetic resonance imaging subgrouping

recently (KJAER et al., 2006). Modic changes were first described by Modic et al. 1988

(MODIC et al., 1988; MODIC and ROSS, 2007), who identified three types (Type I, II and

III). Based on the histological studies, Type I was characterised by fissured endplates and

vascular granulation tissue adjacent to the endplate, whereas Type II was characterised as

disruption of the endplates as well as fatty degeneration of the adjacent bone marrow

(MODIC et al., 1988). Type III appeared to involve sclerosis of the bone marrow as seen on

radiographs (MODIC, MASARYK et al., 1988). Up to date, one review has investigated if

Modic changes constitute a specific subgroup of low back pain (JENSEN and LEBOEUF-

YDE, 2011). However, the inclusion of single subgroup designs (e.g. studies including all

people with Modic changes and no people without Modic changes) prevents a robust

evaluation of whether effect modification occurred in this subgroup (KENT et al., 2010).

If subgroups of patients, based on magnetic resonance imaging findings, who respond

best to specific interventions could be identified, the potential exists to significantly improve

patient outcomes and healthcare system efficiency. Chapter Eight reports on a systematic

review that sought to investigate if the presence of magnetic resonance imaging findings

identifies patients with low back pain who respond better to particular interventions.

34

5. Recruitment for large observational studies of low back pain

There is a need for large-scale well-designed studies evaluating risk factors for low

back pain. Universally, research studies need sufficient participants to ensure statistical

power and validity, but recruitment remains problematic (FAIRHURST and DOWRICK,

1996). Participant recruitment is considered the most difficult aspect of the research process

(BLANTON et al., 2006; BOWER, WILSON and MATHERS, 2007). Previous research has

reported that problems with recruitment are a major reason for the failure of research studies,

leading to wasted research funding (HUNNINGHAKE, DARBY and PROBSTFIELD, 1987).

One major challenge to collecting large quality samples of data is efficient recruitment of

participants to a study (SPAAR et al., 2009).

5.1. Factors that influence recruitment to observational studies

There are many factors that could potentially contribute to successful recruit

participants to an observational study. Previous research has examined methods to increase

the participation of both patients and healthcare professionals to primary care studies, with

much of the research to date focused on randomised controlled trials (RENDELL, MERRITT

and GEDDES, 2007; ROLLMAN et al., 2008). There is limited evidence available to inform

researchers about factors that can influence recruitment to observational studies conducted in

primary care (HAYWARD et al., 2013). To improve the availability of information on

participant recruitment to observational studies, Chapter Nine of this thesis investigates

factors that influence recruitment to an observational study for low back pain.

35

6. Aims of the thesis

The specific aims of this thesis were to:

1. Describe the short and long-term factors that primary care clinicians consider

important in triggering a sudden episode of acute low back pain (Chapter 2)

2. Investigate the increase in risk of an episode of sudden onset, acute back pain

associated with transient exposure to a range of physical and psychosocial factors

(Chapter 3 and 4).

3. Investigate the influence of various weather conditions on risk of low back pain

(Chapter 5).

4. Systematically review whether magnetic resonance imaging findings of the lumbar

spine predict future low back pain in different samples with and without low back

pain (Chapter 6).

5. Examine the prognosis and prognostic factors for patients with chronic low back pain

presenting to a private, community-based, group exercise program (Chapter 7).

6. Investigate if the presence of magnetic resonance imaging findings identifies patients

with low back pain who respond better to particular interventions (Chapter 8).

7. Identify factors that influence recruitment to an observational study (Chapter 9).

36

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45

Chapter Two

Clinicians’ views on factors that trigger a sudden onset of low back pain

Chapter Two is published as:

Steffens D, Maher CG, Ferreira ML, Hancock MJ, Glass T, Latimer J. Clinicians’ views on

factors that trigger a sudden onset of low back pain. European Spine Journal. 2014; 23:512-

519.

46

Statement from co-authors confirming authorship contribution of the PhD candidate

As co-authors of the paper “Clinicians’ views on factors that trigger a sudden onset of low

back pain”, we confirm that Daniel Steffens has made the following contributions:

Conception and design of the research

Data collection

Analysis and interpretation of the findings

Writing of the manuscript and critical appraisal of the content

Christopher G Maher Date: 01.01.2015

Manuela L Ferreira Date: 01.01.2015

Mark J Hancock Date: 01.01.2015

Timothy Glass Date: 01.01.2015

Jane Latimer Date: 01.01.2015

47

ORIGINAL ARTICLE

Clinicians’ views on factors that trigger a sudden onsetof low back pain

Daniel Steffens • Chris G. Maher • Manuela L. Ferreira •

Mark J. Hancock • Timothy Glass • Jane Latimer

Received: 8 August 2013 / Revised: 24 November 2013 / Accepted: 24 November 2013 / Published online: 8 December 2013

� Springer-Verlag Berlin Heidelberg 2013

Abstract

Purpose Little is known about what triggers an episode of

low back pain (LBP) in those presenting to primary care.

Previous studies of risk factors have focused on specific

occupational settings and work conditions. No study has

asked primary care clinicians to consider what triggers an

episode of sudden-onset LBP in patients presenting to them

for care. The purpose of this study, therefore, was to

describe the short- and long-term factors that primary care

clinicians consider important in triggering a sudden epi-

sode of acute LBP.

Methods One hundred and thirty-one primary care clini-

cians who were recruiting patients with LBP to a large

observational study were invited to participate. A ques-

tionnaire was designed to obtain information about the

clinician’s characteristics, profession and clinical experi-

ence. We also asked clinicians to nominate the five short-

and five long-term exposure factors, most likely to trigger a

sudden episode of acute LBP, based on their experience.

Descriptive statistics and frequency distributions were used

to describe clinician’s characteristics and the frequencies of

the main risk factor categories were reported.

Results Based on the views of 103 primary care clini-

cians, biomechanical risk factors appear to be the most

important short-term triggers (endorsed by 89.3 % of cli-

nicians) and long-term triggers (endorsed by 54.2 % of

clinicians) for a sudden episode of acute LBP. Individual

risk factors were endorsed by 39 % of clinicians as

important long-term triggers, while only 6.4 % of clini-

cians considered them important short-term triggers. Other

risk factors, such as psychological/psychosocial and

genetic factors, were not commonly endorsed as risk fac-

tors for an episode of LBP by primary care clinicians.

Conclusions This study shows that primary care clini-

cians believe that biomechanical risk factors are the most

important short-term triggers, while biomechanical and

individual risk factors are the most important long-term

triggers for a sudden onset of LBP. However, other risk

factors, such as psychological/psychosocial and genetic,

were not commonly endorsed as risk factors for an episode

of LBP by primary care clinicians. Results of this study are

based on primary care clinicians’ views and further

investigation is needed to test the validity of these sug-

gested risk factors.

Keywords Low back pain � Primary care � Risk factors �Observational � Epidemiology

Introduction

Low back pain (LBP) is the most common musculoskeletal

condition affecting approximately 80 % of the adult

D. Steffens � C. G. Maher � M. L. Ferreira � J. Latimer

Musculoskeletal Division, The George Institute for Global

Health, Sydney Medical School, The University of Sydney,

Level 13, 321 Kent Street, Sydney, NSW 2000, Australia

D. Steffens (&)


Health, Sydney Medical School, The University of Sydney,

Missenden Road, PO Box M201, Sydney, NSW 2050, Australia

e-mail: [email protected]

M. J. Hancock

Discipline of Physiotherapy, Faculty of Human Sciences,

Macquarie University, 2 Technology Place, Macquarie Park,

Sydney, NSW 2113, Australia

T. Glass

Warwick Medical School, University of Warwick,

Coventry CV4 7AL, UK

123

Eur Spine J (2014) 23:512–519

DOI 10.1007/s00586-013-3120-y

48

population at least once during their lifetime [1, 2]. LBP

troubles are the fifth most frequent reason for a visit to a

primary health care clinician in the USA and the seventh

most frequent reason in Australia [3, 4]. In Australia back

pain is the health condition that carries the greatest burden

when considering lives lived with disability [5]. The global

burden of the condition is enormous and includes high

costs with medical care, loss of productivity and indemnity

payments [6]. Despite this, investigation into risk factors

for LBP is in a developing stage when compared with other

common conditions such as cardiovascular disease and

cancer [7]. A better understanding of factors that trigger an

episode of LBP may provide important insights into the

prevention and management of this condition.

LBP is a complex condition with many factors believed

to contribute to its onset [8]. These factors can be aggre-

gated into a smaller number of categories [9] including

biomechanical factors (regular lifting, exposure to vibra-

tion, physically demanding jobs, bending and twisting,

pushing and pulling heavy loads, awkward posture) [2, 7–

20], psychological/psychosocial factors (job satisfaction,

local support in the workplace, depression, job control,

stress) [2, 7, 9, 16, 19–25] and individual risk factors

(sedentary lifestyle, age, smoking, gender, obesity, poor

general health, marital status, pregnancy) [2, 7, 9, 12, 13,

20, 21, 23, 26–31]. Past studies have investigated many of

these factors and their relationship to LBP. A few studies

have also investigated genetic risk factors [7, 29, 32].

Interestingly, only a small number of studies have exam-

ined risk factors across all four risk factor categories.

While there are many studies of risk factors for LBP [9,

33, 34], most knowledge stems from studies focused on

specific occupational groups and working conditions [8–

10, 12–19, 23]. Although studies conducted in occupational

settings may reveal important risk factors for work-related

back pain, these risks may not be relevant to other popu-

lations such as those drawn from primary care. In addition,

previous studies of LBP have been criticised as being too

narrowly focused on only one or perhaps two of the cate-

gories of individual, biomechanical, psychological/psy-

chosocial and genetic aspects of the problem [12].

Little is known about the causes of LBP in the general

population who present to primary care. The starting point

in evaluating risk factors for LBP in primary care is the

identification of putative risk factors that need to be

investigated. Interviewing primary care clinicians who

frequently manage patients with LBP can provide insight

into what may be the most common triggers for this con-

dition. The aim of this study, therefore, was to describe the

most likely risk factors involving short- and long-term

exposure that primary care clinicians believe could trigger

a sudden episode of acute LBP.

Materials and methods

Data for this study were provided by clinicians recruiting

participants to the TRIGGERS case crossover study [35].

TRIGGERS is an observational study and was designed

to quantify the transient increase in risk of a sudden

episode of LBP associated with acute exposure to a

range of common physical and psychological factors

[35].

Study sample

Participants in the study were 131 primary care clinicians

(physiotherapists and chiropractors) who were recruiting

patients for the TRIGGERS study from October 2011 to

November 2012 in NSW, Australia.

Recruitment

Clinicians were contacted and invited to participate by

e-mail. In the e-mail, we attached the invitation letter,

consent form and a one-page questionnaire. The invitation

letter consisted of a brief explanation of the study methods

and aims. Clinicians who consented to participate were

instructed to answer the one-page questionnaire based on

their clinical experience and send it back to the research

team. Clinicians who had not responded within 2 weeks

were contacted by a study researcher and again invited to

participate. Ethical approval for the study was granted by

the University of Sydney Human Research Ethics

Committee.

Data collection

A one-page self-administered questionnaire was designed

to obtain information about the clinician’s characteristics

(gender, age and address), profession (physiotherapist or

chiropractor) and clinical experience (years as practising

clinician and years managing LBP). Two items were used

to measure their beliefs about triggers for LBP. These

were:

1. Based on your clinical experience, list what you

consider to be the five most likely factors involving

short-term exposure that are triggers for a sudden

episode of acute low back pain?

2. Based on your clinical experience, list what you

consider to be the five most likely factors involving

long-term exposure that increase the risk of a sudden

episode of acute low back pain?

All questionnaires were returned by e-mail and the

answers entered in the study database.

Eur Spine J (2014) 23:512–519 513

123

49

Risk factors categories

We developed descriptive categories to code the free text

responses based upon published risk factor studies. A

search from the earliest record to January 2013 was

undertaken on PubMed to identify relevant studies using

the following keywords: low back pain, backache, lum-

bago, risk factors, causality, aetiology and epidemiology.

Abstracts were retrieved and examined. Reported risk

factors were extracted and entered into a table. Figure 1

describes the categories we developed including main

category (or aggregate label) and the sub-categories

(Table 1).

Coding short- and long-term risk factors

Two researchers individually coded the free text answers

about short- and long-term exposures that may be a

trigger for a sudden episode of acute LBP. The free text

responses were first coded into five main categories

(Fig. 1):

1. Individual risk factors

2. Biomechanical risk factors

3. Psychological/psychosocial risk factors

4. Genetic risk factors

5. Other risk factors

Fig. 1 Diagram of risk factors for low back pain

514 Eur Spine J (2014) 23:512–519

123

50

The same researchers then coded the free text responses

into sub-categories. Each nominated risk factor was only

classified once into a main category and a sub-category

(e.g. 1: Smoking was first categorised as an ‘‘individual

risk factor’’ and then sub-categorised into ‘‘smoking’’. e.g.

2: Golf was first categorised as a ‘‘biomechanical risk

factor’’ and then sub-categorised into ‘‘sport injuries’’). In

case of disagreement, a third researcher was consulted and

a decision was made by consensus.

Statistical analysis

To check the reliability of the coding of free text data, we

compared the independent coding of the two researchers.

Inter-rater reliability was expressed using percentage exact

agreement and Cohen’s kappa [36] for the main categories

and sub-categories.

Descriptive statistics and frequency distributions were

calculated to describe the characteristics of the clinicians

and the frequencies that the main risk factor categories

were reported (individual, biomechanical, psychological/

psychosocial, genetic and other risk factors).

The clinicians’ endorsement of various categories of

triggers (main categories and sub-categories) was exam-

ined using the Chi-squared (v2) statistic. All analyses were

performed using the statistical package SPSS for Windows

version 21 (SPSS, Inc., Chicago, IL) with a significance

level set at 0.05.

Results

Of the 131 clinicians invited to participate in the study, 103

(79 %) completed the questionnaire. The characteristics of

the participating clinicians are described in Table 2. The

mean age was 43 years (range 23–65), clinical experience

managing LBP was 18 years (range 1–40) and slightly

more were male (55 %).

In general, the reliability between the two independent

researchers who coded the short- and long-term risk factor

categories was very good (Table 2). The observed agree-

ment ranged from 89 to 99 % and the inter-rater reliability

ranged from substantial (j = 0.71) to almost perfect

agreement (j = 0.95) [36].

Short- and long-term main categories risk factors

Table 3 lists the frequency of endorsement of the main

short- and long-term risk factor categories. Based on the

views of 103 primary care clinicians, biomechanical risk

factors appear to be the most important short-term triggers

(endorsed by 89.3 % of clinicians) and long-term triggers

(endorsed by 54.2 % of clinicians) for a sudden episode of

acute LBP. Individual risk factors were endorsed by 39 %

of clinicians as important long-term triggers, while only

6.4 % of clinicians considered them important short-term

triggers. Only one clinician reported genetics (0.2 %) as a

long-term risk factor for acute LBP. Chi-square tests con-

firmed a significant difference in proportions of the main

short- and long-term risk factor categories (v2 = 180.70,

p \ 0.001). While biomechanical factors were considered

the most important short- and long-term risk factors,

individual factors were endorsed far more commonly as

long-term risk factors.

Table 1 Clinicians’ characteristics (n = 103)

Characteristics n (%) or mean ± SD

Gender (male) 56 (55 %)

Age (years) 43 ± 10

Profession

Physiotherapist 102 (99 %)

Chiropractor 1 (1 %)

Current position

Principal/owner 45 (44 %)

Clinician/senior clinician 58 (56 %)

Clinical experience (years) 19 ± 10

Clinical experience managing LBP (years) 18 ± 9

Table 2 Reliability between researchers A and B

Risk factors categories Observed agreement (%) ja

Short-term main categories 99 0.95

Short-term sub-categories 96 0.89

Long-term main categories 94 0.88

Long-term sub-categories 89 0.71

a Interpretation: 0.01–0.20 slight agreement; 0.21–0.40 fair agree-

ment; 0.41–0.60 moderate agreement; 0.61–0.80 substantial agree-

ment; 0.81–0.99 almost perfect agreement [36]

Table 3 Frequency of main risk factors stratified by short and long

term

Main categories risk factors Short terma Long terma

N % N %

Individual 33 6.4 201 39

Biomechanical 460 89.3 279 54.2

Psychological/psychosocial 3 0.6 16 3.1

Genetic 0 0.0 1 0.2

Other risk factors 9 1.7 8 1.6

Missing data 10 1.9 10 1.9

Total 515 100 515 100

a v2 = 180.70, p \ 0.001

Eur Spine J (2014) 23:512–519 515

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Short- and long-term sub-categories risk factors

Table 4 lists the frequency of endorsement of short- and

long-term sub-category risk factors for acute LBP. Lifting

(17.5 %) was the most frequently endorsed short-term sub-

category risk factor, followed by prolonged sitting (9.1 %)

and physical trauma (8.9 %). For long-term sub-category

risk factors, prolonged sitting (13.4 %) was most frequently

endorsed followed by lifting (10.9 %) and physical inactiv-

ity (9.1 %). Similarly to the analysis of the main categories,

the Chi-square test (v2 = 360.456, p \ 0.001) suggested

that there was a difference between short- and long-term sub-

category risk factors. Obvious sub-category differences

included physical trauma and physical inactivity for short

and long term; physical trauma was endorsed more fre-

quently as a short-term risk factor, while inactivity was

endorsed more commonly as a long-term risk factor.

Discussion

Statement of principal findings

Based on the opinions of 103 primary care clinicians, the

most important main short- and long-term risk factors to

trigger an episode of sudden acute LBP are biomechanical

(89.3 and 54.2 %, respectively) and individual risk factors

(6.4 and 39 %, respectively). Surprisingly, other risk factors,

such as psychological/psychosocial and genetic factors,

were not commonly endorsed as risk factors for an episode of

LBP by primary care clinicians. Some of the most frequently

reported short- and long-term sub-categories to trigger a

sudden episode of acute LBP are lifting (17.5 and 10.9 %,

respectively) and prolonged sitting (9.1 and 13.4 %,

respectively).

Strengths and weaknesses of the study

We were able to interview a considerable number of

experienced primary care clinicians currently treating

patients with LBP. In addition, we identified a range of

factors that are considered triggers involving short- and

long-term exposures. The reliability between the two

independent researchers who coded the short- and long-

term risk factor categories was very good with the inter-

rater reliability ranging from substantial to almost perfect

agreement [36]. However, the results of the study are based

on primary care clinicians’ views and further investigation

is needed to test the validity of these suggested risk factors.

Comparison to others studies

To our knowledge, this is the first observational study that

has interviewed primary care clinicians to determine their

views on short- and long-term triggers for a sudden episode

of acute LBP in the general population. Most of the pre-

vious studies on risk factors for LBP tended to focus on

specific triggers and included samples from occupational

settings. There is a research focus on biomechanical [2, 7–

20], psychological/psychosocial [2, 7, 9, 16, 19–25] and

Table 4 Frequency of risk factor sub-categories stratified by short

and long term

Risk factors sub-categories Short terma Long terma

N % N %

Lifting 90 17.5 56 10.9

Prolonged sitting 47 9.1 69 13.4

Physical trauma 46 8.9 3 0.6

Bending 41 8.0 24 4.7

Unaccustomed activity 38 7.4 2 0.4

Other biomechanical risk factors 27 5.2 28 5.4

Sport injuries 24 4.7 9 1.7

Gardening 20 3.9 2 0.4

Bending and twisting 17 3.3 6 1.2

Twisting 14 2.7 4 0.8

Coughing/sneezing 12 2.3 1 0.2

Lifting and twisting 12 2.3 0 0.0

Lifting and bending 12 2.3 8 1.6

Driving 11 2.1 15 2.9

Bending and twisting while lifting 10 1.9 2 0.4

Sudden movements 8 1.6 1 0.2

Other risk factors 9 1.7 8 1.6

Prolonged standing 6 1.2 16 3.1

Unexpected load 6 1.2 0 0.0

Repetitive movements 5 1.0 8 1.6

Other individual risk factors 4 0.8 30 5.8

Pulling/pushing 5 1.0 2 0.4

Pregnancy/childbirth 3 0.6 13 2.5

Previous LBP episodes 2 0.4 15 2.9

Diminished trunk muscle strength and

fatigability

2 0.4 22 4.3

Spine/pelvis/lower limb impairment 2 0.4 23 4.5

Sedentary work 2 0.4 14 2.7

Stress 2 0.4 9 1.7

Overweight 1 0.2 25 4.9

Spine/pelvis/lower limb pathology 1 0.2 11 2.1

Physical inactivity 0 0.0 47 9.1

Less frequent risk factorsb 26 5.0 32 6.2

Missing data 10 1.9 10 1.9

Total 515 100 515 100

Bold top five short and long risk factor sub-categoriesa v2 = 360.456, p \ 0.001b Risk factors with a grouped frequency count B5 were combined

516 Eur Spine J (2014) 23:512–519

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52

individual risk factors [2, 7, 9, 12, 13, 20, 21, 23, 26–31]

for LBP; however, only a few studies investigated risk

factors from all domains together [7].

Findings from our study suggest that the views of cli-

nicians are as variable as in the evidence found in the

literature. Our study found that biomechanical risk factors,

such as lifting, prolonged sitting and bending, were con-

sidered by primary care clinicians to be important risk

factors for the onset of LBP, in accordance with previous

studies [10, 15, 26, 37]. On the other hand, individual risk

factors, such as physical inactivity, have only weak support

in the literature as a risk factor for developing LBP [27,

29]. This is in contrast to the study clinicians who con-

sidered physical inactivity as a common long-term risk

factor for LBP. Although psychological/psychosocial and

genetic risk factors did not appear to be endorsed strongly

by the primary care clinicians interviewed in this study,

there is strong evidence in the literature suggesting the

opposite [12, 22, 37]. However, this inconsistency between

the present study and the literature may be due to the dif-

ferent settings in which the studies were performed and/or

clinician’s lack of awareness about the importance of

psychological risk factors. Psychological/psychosocial

factors may be more important in occupational settings

than in primary care. Conversely, individual risk factors

may be more important in primary care settings than

occupational settings.

Meaning of the study: possible mechanisms

and implications for clinicians

Based on the opinion of primary care clinicians, the most

likely short-term risk factors for triggering an episode of

LBP are, by far, the biomechanical risk factors and the

most likely causes involving long-term exposure are indi-

vidual and biomechanical risk factors. This is somewhat

inconsistent with the literature [27, 29]. The reasons why

experienced clinicians think such factors are important may

be due to the fact that they are seeing a general sample of

the population, while previous studies tend to focus on

occupational settings. One other reason may be that pri-

mary care clinicians have limited expertise in assessing

psychosocial/psychological and genetic factors as likely

triggers for an onset of LBP.

A better understanding of the most endorsed risk factors

for LBP in primary care will help clinicians to improve

patient treatment and also provide important advice in

prevention of future LBP episodes.

Unanswered questions and future research

Future studies should investigate risk factors for LBP in

samples of the general population and simultaneously

investigate all main categories of risk factors found to

trigger an episode of LBP (individual, biomechanical,

psychosocial/psychological, genetic and others risk fac-

tors). There is also a need to investigate the combination of

two or more risk factors. Previous studies have confirmed

that a combination of two or more risk factors (i.e. poor

posture, repetitive lifting and high job strain) are com-

monly identified in the same individual [23]. Increasing our

understanding of what triggers an episode of LBP will

enable us to design better prevention programs. Future

research could involve the modification of endorsed trig-

gers in a clinical trial to determine the effectiveness in

reducing future episodes of LBP. In addition, there is a

need to determine whether psychological/psychosocial

features are important risk factors in the primary care set-

ting using rigorous prospective cohort designs.

Conclusions

Based on primary care clinicians’ opinion, biomechanical

risk factors are the most important short-term triggers,

while biomechanical and individual risk factors are the

most important long-term triggers for sudden-onset LBP.

Psychological/psychosocial and genetic risk factors were

not considered important risk factors by primary care cli-

nicians. Findings from this study should be further inves-

tigated to better understand short- and long-term exposures

that are triggers for an acute sudden episode of LBP. This

information will help inform LBP prevention programs.

Conflict of interest None.

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Chapter Three

Triggers for an episode of sudden onset low back pain: study protocol

Chapter Three is published as:

Steffens D, Ferreira ML, Maher CG, Latimer J, Koes BW, Blyth FM, Ferreira PH. Triggers

for an episode of sudden onset low back pain: study protocol. BMC Musculoskeletal

Disorders. 2012; 24:13-17.

56


As co-authors of the paper “Triggers for an episode of sudden onset low back pain: study

protocol”, we confirm that Daniel Steffens has made the following contributions:






Bart W Koes Date: 01.01.2015

Fiona M Blyth Date: 01.01.2015

Paulo H Ferreira Date: 01.01.2015

57

STUDY PROTOCOL Open Access

Triggers for an episode of sudden onset low backpain: study protocolDaniel Steffens1, Manuela L Ferreira1, Christopher G Maher1*, Jane Latimer1, Bart W Koes2, Fiona M Blyth3 andPaulo H Ferreira4

Abstract

Background: Most research on risk factors for low back pain has focused on long term exposures rather thanfactors immediately preceding the onset of low back pain. The aim of this study is to quantify the transientincrease in risk of a sudden episode of low back pain associated with acute exposure to a range of commonphysical and psychological factors.

Methods/design: This study uses a case-crossover design. One thousand adults with a sudden onset of low backpain presenting to primary care clinicians will be recruited. Basic demographic and clinical information includingexposure to putative triggers will be collected using a questionnaire. These triggers include exposure to hazardousmanual tasks, physical activity, a slip/trip or fall, consumption of alcohol, sexual activity, being distracted, and beingfatigued or tired. Exposures in the case window (0-2 hours from the time when participants first notice their backpain) will be compared to exposures in two control time-windows (one 24-26 hours and another 48-50 hoursbefore the case window).

Discussion: The completion of this study will provide the first-research based estimates of the increase in risk of asudden episode of acute low back pain associated with transient exposure to a range of common factors thoughtto trigger low back pain.

BackgroundNearly 4 million people in Australia suffer from backpain at any one time [1], with total treatment costsexceeding $1 billion a year [2]. In the US, the figure isan astonishing US$32 billion a year [3]. Back complaintsare the seventh most common condition in patientsconsulting general practitioners in Australia, and themost common musculoskeletal condition [4]. It is alsothe most common health problem for which an imagingtest is ordered by a general practitioner [4].A potential solution to managing the problem of low

back pain is the identification and control of modifiablerisk factors. This approach is appealing and seeminglylogical and there are notable examples where such anapproach has provided major improvements in publichealth. For back pain this approach has not yet been

fruitful: Cochrane reviews of workplace interventions[5], insoles [6] and lumbar supports [7] have failed tosupport these traditional back pain preventionapproaches. Prevention strategies have to date been lar-gely based on controlling long-term exposure to riskfactors, for example, modifying seats to control vibrationin truck drivers. However it is likely that the full poten-tial of prevention will not be reached unless we alsoconsider commonly occurring, modifiable risk factorsthat happen just before the onset of back pain. In thisregard we see our proposed research as complementaryto, rather than in conflict with, research evaluating longterm risk factors.The existence of short term risk factors or ‘triggers’ is

consistent with the time course of back pain. It is wellestablished that most people will experience low backpain in their lifetime [8], that pain is typically recurrent[9] and that episodes are usually of sudden onset [10].For example research conducted by our group demon-strated that in an inception cohort of 969 subjects, 82%reported that their onset of low back pain was sudden

* Correspondence: [email protected] division, The George Institute for Global Health, SydneyMedical School, The University of Sydney, PO Box M201, Missenden Road,Sydney, New South Wales 2050, AustraliaFull list of author information is available at the end of the article

Steffens et al. BMC Musculoskeletal Disorders 2012, 13:7http://www.biomedcentral.com/1471-2474/13/7

© 2012 Steffens et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative CommonsAttribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction inany medium, provided the original work is properly cited.

58

mailto:[email protected]

http://creativecommons.org/licenses/by/2.0

[10]. This pattern of low back pain suggests that ratherthan solely looking at long term exposure to risk factorsit would be instructive to also look closely at eventsoccurring immediately prior to the episode to identifymodifiable triggers to the episode. This information isroutinely sought by health practitioners when a patientwith low back pain seeks care. The treating cliniciancommonly asks the patient what activity they were per-forming just prior to the onset of pain, in essence, “wasthe episode triggered by something unusual that hap-pened just before?” The scientific method best suited toanswer this question is the case-crossover design [11].We will use the case-crossover design to provide the

first accurate estimates of the transient increase in riskof low back pain associated with transient exposure tovarious triggers. It is possible that we will identify sev-eral factors that are not modifiable but this informationwill be extremely important to our understanding andexplanation of the causes of low back pain.

Study Aims1) To quantify the transient increase in risk of an epi-sode of sudden onset, acute, low back pain associatedwith exposure to a range of common physical and psy-chological factors listed in Table 1.2) To determine if habitual physical activity moderates

the transient increase in risk of an episode of suddenonset, acute, low back pain associated with exposure tothe physical and psychological factors listed above.

Methods/DesignThe study will use the case-crossover design. The case-crossover design enables quantification of the risk asso-ciated with transient exposures [12]. It is more efficientthan cohort designs because it samples only cases, andmay be less exposed to selection bias than case-controldesigns because cases provide their own control data.

Cases will be identified from patients presenting to pri-mary care seeking treatment for an episode of suddenonset, acute, low back pain. In the case crossover designthe time of the onset of low back pain is identified andthen data are obtained on exposure to a series of possi-ble risk factors in the two hour period prior to theonset of low back pain (case window). Additional dataare obtained on exposures to the same set of possiblerisk factors in an earlier period (24-26 and 48-50 hoursprior to the case window) that did not precede an epi-sode of low back pain (these are referred to as the con-trol windows).The study has been approved by the Human Research

Ethics Committee at the University of Sydney (protocolnumber 05-2011/13742) and has received funding fromAustralia’s National Health and Medical Research Coun-cil (application ID APP1003608).

Study ParticipantsOne thousand consecutive patients (study participants)presenting to primary care clinicians (general medicalpractitioners, physiotherapists, chiropractors and phar-macists) for treatment of an episode of sudden onset,acute, low back pain will be recruited in Sydney, Austra-lia. Primary care clinicians will be trained individually orin small groups on the study methods and procedures.Study participants must be 18 years of age (or older) toparticipate.To be eligible to enter the study participants must

meet the criteria below:

▪ Comprehends spoken English;▪ Primary complaint of pain in the area between the12th rib and buttock crease, with or without leg pain;▪ Pain at least moderate intensity during the first 24hours of the episode (assessed using a modified ver-sion of item 7 of the SF36);

Table 1 Factors that may trigger an episode of low back pain to be evaluated in the study

Physical Factors Hazardous manual tasks:

- tasks involving heavy loads;

- tasks involving awkward postures;

- tasks involving objects that could not be positioned close to the body;

- tasks involving live people or animals;

- tasks involving loads that are unstable, unbalanced or difficult to grasp or hold;

Vigorous physical activity

Moderate physical activity

A slip/trip or fall

Consumption of alcohol

Sexual activity

Psychological Being distracted

Factors Being fatigued or tired


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▪ Presentation for treatment within 7 days from thetime of pain onset;▪ Not have known or suspected serious spinalpathology (eg metastatic, inflammatory or infectivediseases of spine, cauda equina syndrome, spinalfracture);

An episode of acute low back pain will be defined asan episode preceded by a period of at least one monthwithout low back pain where the participant was notconsulting a health care practitioner or continuing withmedication for their low back pain (in accordance withthe De Vet et al. [13] definition of an ‘episode’ of acutelow back pain). A sudden onset episode of low backpain will be defined as pain of at least moderate inten-sity that developed over the first 24 hours (assessedusing a modified version of item 7 of the SF36).To describe further the cohort of study clinicians, we

will collect descriptive data, including the clinician’s age,contact details, current position and past clinical experi-ence. Secondly, we are collecting information regardingwhat clinicians in general consider as possible triggersfor a new episode of back pain. Based on their clinicalexperience, they are asked to list the five most likelytriggers for a sudden onset episode of low back pain.They will consider both (i) short term and (ii) long termexposures (see additional file 1). These data will be usedto inform the categorisation of putative risk factors inthe analyses of our participant data, and to assesswhether opinions of the study participants regardingpossible triggers for their low back pain are analogouswith their clinicians’ perceptions.

Participant recruitmentPatients seeking care for acute low back pain that fulfilthe inclusion criteria and agreeing to participate will bereferred to the study and their details (screening formand consent form) will be sent by fax to the study office.A study researcher will receive the fax and contact theparticipant as soon as possible to perform the studyinterview. Patients not able to answer the study ques-tionnaire in seven days from the time their clinicianreferred them to the study will be excluded.Prior to the study interview, the researchers will dou-

ble-check the eligibility criteria and explain the natureof the study to the participant. Participants are able towithdrawn from the study at any time.

Study interviewThe interview is divided into two parts. In the first partwe will collect basic demographic and clinical data andin the second part, we will collect information on puta-tive triggers (see additional file 2). We will record thedate and time when the patient first noticed their back

pain. Where possible, using a diary, calendar and/orsmartphone, we will then ask them to recall what theywere doing in the three days leading up to the onset oftheir back pain and also on the day of their back pain.Following this we will ask about exposure to the pre-

viously mentioned putative triggers. Where subjectsrespond affirmatively we collect detailed information onthe trigger, time and duration in free text. We will alsoask the study participant to consider what they thinkmay have triggered their LBP and similarly recorddetailed information on the nominated trigger, time andduration in free text.When asking the study participant about exposure to

specific triggers we have developed a script to lead theinterview (see additional file 2).

BlindingClinicians and study participants will be blinded to thecase and control periods. The study questionnaire isdesigned to investigate exposure to triggers over alonger time period than will be used in the analysis sothat participants in the trial remain blind to the dura-tion of the case and control windows. For example par-ticipants will be asked about their exposures for threedays preceding their back pain and also on the day oftheir back pain. A random sample of telephone calls willbe audited and the congruency of the log and telephonecall checked by the investigators. Data entry into thedatabase will be conducted by a separate person whowill be blinded to all putative risk factors. Blinding maybe less important in case-crossover designs than case-control studies because in the case-crossover design par-ticipants report exposure to triggers in both the case andcontrol windows. Recall bias can only occur if there isdifferential mis-reporting in the case and control win-dows. In our opinion this is unlikely.

Statistical analysisThe analyses follows standard methods for stratifiedanalyses [12] with the individual subject the stratifyingvariable in a case-crossover design. The estimates ofrelative risk are based on the ratio of the observed fre-quency of exposure to each of the transient triggers dur-ing the case period, to the expected frequency ofexposure during the two control periods. This is knownas a matched-pair interval approach where contrasts aremade between a pair of case control periods contributedby the same subject. In our proposed study there will betwo matched-pair intervals.To analyse the matched-pair interval data we will use

standard methods for case-control data (Mantel-Haens-zel estimator). Instead of having concordant and discor-dant pairs of subjects, the pairs will consist of twointervals for each subject, a case period (2 hours prior


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to the event) and a control period (24-26 hours prior tothe event). A subject’s pair of intervals will either beconcordant or discordant with respect to each of thetriggers nominated on the item list. Ninety-five percentconfidence intervals will be computed by exact methodsbased on the binomial distribution. Comparison withthe first control period will form the primary analyses.Secondary analyses will be performed as describedabove but using the second control period (48-50 hoursprior to the event) as the control data for the matched-pair interval.

Sample sizeThe study was designed to be adequately powered forthe primary analysis, which involves estimation of therisk associated with transient exposure to the differenttypes of triggers. We calculated the sample size neces-sary for a paired case-control study using the proceduresdescribed by Dupont [14]. This showed that in a con-ventional paired case-control design with alpha set at0.05 we would need a sample of 1,000 cases to providean 80% probability of detecting an odds ratio of 1.5 orgreater across the plausible range of exposure preva-lence’s in control windows (0.2 to 0.8) and plausiblerange of correlations between exposure in case and con-trol windows (0.0 to 0.5).

DiscussionThis case cross-over study will provide the first-researchbased estimates of the transient increase in risk of asudden onset, acute, episode of low back pain associatedwith transient exposures to a range of physical and psy-chological factors. We anticipate that we will identifyseveral modifiable factors that are triggers for an episodeof low back pain. This information will be invaluable indesigning future prevention strategies, and enabling clin-icians to give evidence based advice to patients keen toavoid future episodes of low back pain.Recall bias is a major limitation of retrospective stu-

dies. Participants may under or overestimate the usualfrequency of exposures to the time of the injury (casewindow). They may also under or overestimate exposurein the case control windows because of memory lapse ordifficulty in estimating exposure. In this study, partici-pants must have presented for care within seven days ofthe onset of the injury to facilitate recall of activities. Inaddition, our questionnaire asks participants to useprompts such as referring to their agenda, calendar and/or smartphones to stimulate their memory of the activ-ities they performed in the days prior to the onset oftheir low back pain.The completion of this trial is expected by early 2014.

Additional material

Additional file 1: Clinicians’ questionnaire. Questionnaire to beapplied to describe further the cohort of study clinicians.

Additional file 2: Study Participants’ Questionnaire. Questionnaire tobe applied to the study participants.

AcknowledgementsThe TRIGGERS study team includes Anurina Das. We would like toacknowledge the valuable contribution of Qiang Li to the study statisticalanalysis plan. The National Health and Medical Research Council (NHMRC),Australia, provides funding for this study.

Author details1Musculoskeletal division, The George Institute for Global Health, SydneyMedical School, The University of Sydney, PO Box M201, Missenden Road,Sydney, New South Wales 2050, Australia. 2Department of General Practice,Erasmus MC, PO Box 2040, 3000 CA Rotterdam, The Netherlands. 3Centre forEducation and Research on Ageing, The University of Sydney, C 22 -Concord Hospital, Sydney, New South Wales 2006, Australia. 4Discipline ofPhysiotherapy, Faculty of Health Sciences, The University of Sydney, PO Box170, Lidcombe 1825, Syndey, New South Wales, Australia.

Authors’ contributionsCGM, JL, MLF, BWK, FMB and PHF are the principal investigators - togetherthey conceived and designed the trial and procured funding. DS and MLFdrafted the first version of the manuscript. All authors contributed to thewriting of the manuscript. All authors read and approved the final version ofthe manuscript.

Competing interestsThe authors declare that they have no competing interests. Prof Maher andA/Prof Latimer’s fellowships are funded by the Australian Research Council.

Received: 24 December 2011 Accepted: 24 January 2012Published: 24 January 2012

References1. Australian Institute of Health and Welfare: Arthritis and musculoskeletal

conditions in Australia. Canberra: Australian Institute of Health and Welfare;2005.

2. Walker B, Muller R, Grant W: Low back pain in Australian adults: theeconomic burden. Asia Pac J Public Health 2003, 15(2):79-87.

3. Agency for Healthcare Research and Quality: Total Expenses and PercentDistribution for Selected Conditions by Type of Service: United States.Medical Expenditure Panel Survey Household Component Data; 2005.

4. Britt H, Miller G, Knox S, Charles J, Pan Y, Henderson J, Baryram C, Valenti L,Ng A, O’Halloran J: General practice activity in Australia 2004-2005.Canberra: Australian Institute of Health and Welfare; 2005.

5. Van Oostrom S, Driessen M, de Vet H, Franche R, Schonstein E, Loisel P, VanMechelen W, Anema J: Workplace interventions for preventing workdisability. Cochrane Database of Systematic Reviews 2009.

6. Sahar T, Cohen MJ, Ne’eman V, Kandel L, Odebiyi D, Lev I, Brezis M,Lahad A: Insoles for prevention and treatment of back pain. CochraneDatabase of Systematic Reviews 2007, , 4: CD005275.

7. Van Duijvenbode I, Jellema P, Van Poppel MN, Van Tulder MW: Lumbarsupports for prevention and treatment of low back pain. CochraneDatabase of Systematic Reviews 2008, 2.

8. Waddell G: The Back Pain Revolution. Edinburgh: Churchill Livingstone;, 22004.

9. Von Korff M, Saunders K: The course of back pain in primary care. Spine1996, 21(24):2833-2839.

10. Henschke N, Maher CG, Refshauge KM: A systematic review identifies fivered flags to screen for vertebral fracture in patients with low back pain.J Clin Epidemiol 2008, 61(2):110-118.

11. Maclure M, Mittleman M: Should we use a case-crossover design? AnnuRev Public Health 2000, 21:193-221.


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http://www.biomedcentral.com/content/supplementary/1471-2474-13-7-S1.DOCX

http://www.biomedcentral.com/content/supplementary/1471-2474-13-7-S2.DOCX

http://www.ncbi.nlm.nih.gov/pubmed/15038680?dopt=Abstract






12. Maclure M: The case-crossover design: a method for studying transienteffects on the risk of acute events. Am J Epidemiol 1991, 133:144-153.

13. de vet H, Heymans M, Dunn K, Pope D, van der Beek A, Macfarlane G,Bouter L, Croft P: Episodes of low back pain. A proposal for uniformdefinitions to be used in research. Spine 2002, 27(21):2409-2416.

14. Dupont W: Power calculations for matched case-control studies.Biometrics 1988, 44:1157-1168.

Pre-publication historyThe pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2474/13/7/prepub

doi:10.1186/1471-2474-13-7Cite this article as: Steffens et al.: Triggers for an episode of suddenonset low back pain: study protocol. BMC Musculoskeletal Disorders 201213:7.

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http://www.biomedcentral.com/1471-2474/13/7/prepub

Name: ___________________________________________________________________

Gender: □ Female □ Male Date of Birth: _____________________________

Address: ________________________________________________________________

Phone:_____________________________ FAX: ________________________________

Email:_____________________________

Profession (tick one)

physiotherapist medical practitioner pharmacist

Current Position:__________________________________________________________________

Clinical experience

Years as practicing clinician _______________________________

Years managing low back pain ______________________________

1. Based on your clinical experience, list what you consider to be the five most likely

factors involving short term exposure that are triggers for a sudden episode of acute

low back pain? (E.g. in my clinical experience, running 15km on the road with poor shoes

can trigger an episode of shin splints).

1)________________________________________________________________________

2)________________________________________________________________________

3)________________________________________________________________________

4)________________________________________________________________________

5)________________________________________________________________________

2. Based on your clinical experience, list what you consider to be the five most likely

factors involving long term exposure that increase the risk of a sudden episode of

acute low back pain (e.g. in my clinical experience working with a ‘poke neck’ posture

increases the risk of neck pain and headaches).

1)________________________________________________________________________

2)________________________________________________________________________

3)________________________________________________________________________

4)________________________________________________________________________

5)________________________________________________________________________

Additional file 1 – Clinicians’ Questionnaire

63

Triggers Specific Questions Tick the boxes where the participant reports pain on the mannequin below:

Height (cm): ______________________ Weight (Kg): _____________________

How much back pain have you had during the first 24 hours of this episode? [1]

None Very mild Mild Moderate Severe Very Severe

During the first 24 hours of this episode how much did back pain interfere with your

normal work (including both work outside the home and housework)? [1]

Not at all A little bit Moderately Quite a bit Extremely

How tense or anxious have you felt in the past week? Circle one. [2]

0 1 2 3 4 5 6 7 8 9 10

Appendix 5. Study Questionnaire

Calm and

relaxed

As

tense/anxious

as I’ve ever

felt

64

Physical Activity [3]

1. In the last week, how many times have you walked continuously, for at least 10 minutes, for

recreation, exercise or to get to or from places? ______times;

And in the week before your low back pain started? ______times.

What do you estimate was the total time that you spent walking in this way in the last week?

______hours ______minutes;

And in the week before your low back pain started? ______ hours ______minutes.

2. In the last week, how many times did you do any vigorous physical activity which made

you breathe harder or puff and pant? (e.g. jogging, cycling, aerobics, competitive

tennis)______times;


What do you estimate was the total time that you spent doing this vigorous physical activity in

the last week? ______hours ______minutes;


3. In the last week, how many times did you do any moderate physical activities that you have

not already mentioned? (e.g. gentle swimming, social tennis, golf)______times;


What do you estimate was the total time that you spent doing these activities in the last week?


And in the week before your back pain started? ______ hours ______minutes.

4. Was your level of physical activity last week typical for you? Yes No

65

Triggers Exposure

Please write the date and time you first noticed your low back pain on the table below:

Day Fri Sat Sun Mon Tues Wed Thurs Fri Sat Sun

Date

Time

I am going to ask you to recall what you were doing in the three days leading up to

your back pain and also on the day of your back pain. To help your memory I

would like you to sit down with your diary and smartphone. To help make sure we

have the right days I want you to tell me the day, weather and a key thing you did

on each day.

Example: Tuesday: cold and wet; visited parents

Day of back pain: _______________________________________________________

Day before: ____________________________________________________________

2 days earlier: __________________________________________________________

3 days earlier: __________________________________________________________

66

1a. MANUAL TASKS …

HEAVY LOADS [4]

Day

If yes, precisely describe manual task (type of task,

load, duration and time). e.g. Lifted 50 large boxes,

one at a time, (~15kg each box – perceived as heavy)

from the floor and placed them on a bench at waist

height. 8:00am - 20min.

The first group of questions is

about manual tasks. Manual tasks

include lifting, lowering, pushing,

carrying or otherwise moving,

holding or restraining any person,

animal or item.

Firstly we are interested in manual

tasks involving HEAVY LOADS.

So on the day of your back pain did

you engage in any manual tasks

involving a heavy load?

That was the (restate their

description of the day).

Now what about the day before….



OK now two days back That was

the (restate their description of the

day).

OK finally three days back That was


day)

Day of back

pain

Yes No

Day before

Yes No

2 days earlier

Yes No

3 days earlier

Yes No

67

1b. MANUAL TASKS…

AWKWARD POSTURE [4] Day

If yes, precisely describe manual task and posture (type

of task, load, duration, time & body position). e.g. knelt

down while gardening. 2:00pm – 40min.

Now I want you to think about

manual tasks involving an

AWKWARD POSTURE.



involving an awkward position?






OK now two days back That was the

(restate their description of the day).



day)

Day of back

pain

Yes No

Day before

Yes No

2 days

earlier

Yes No

3 days

earlier

Yes No

68

1c. MANUAL TASKS…

AN OBJECT THAT COULD

NOT BE POSITIONED CLOSE

TO THE BODY [4]

Day


of task, load, duration, time and body position). e.g.

Lifted large box (~7Kg – perceived as light) out of the

car boot and placed it on the floor. 11:00am – 10 sec.


manual tasks involving AN

OBJECT THAT COULD NOT BE

POSITIONED CLOSE TO THE

BODY.



involving an object that could not

be positioned close to the body?










day)

Day of back

pain

Yes No

Day before

Yes No

2 days

earlier

Yes No

3 days

earlier

Yes No

69

1d. MANUAL TASKS…

LIVE PEOPLE OR ANIMALS [4] Day



Lifted 2 year-old child (~12kg – perceived as moderate)

from the floor onto the bed. 8:00pm once. Lifted and

carried baby (5 kg perceived as light), 3 to 4 times from

one room to another. 8:10pm – 30min


manual tasks involving LIVE

PEOPLE OR ANIMALS.



involving live people or animals?

That was the (restate their description

of the day).



of the day).

OK now two days back…


of the day).

OK finally three days back…


of the day)

Day of back

pain

Yes No

Day before

Yes No

2 days

earlier

Yes No

3 days

earlier

Yes No

70

1e. MANUAL TASKS…

A LOAD THAT WAS

UNSTABLE, UNBALANCED OR

DIFFICULT TO GRASP OR

HOLD [4]

Day



lifted a 4 meter extension ladder (~12 Kg – perceived as

moderate) from the car roof racks, carried to garage

and hung on wall. 3:00pm - 5min.


manual tasks involving A LOAD

THAT WAS UNSTABLE,

UNBALANCED OR DIFFICULT

TO GRASP OR HOLD.



involving a load that was unstable,

unbalanced or difficult to grasp or

hold?











description of the day)

Day of back

pain

Yes No

Day before

Yes No

2 days

earlier

Yes No

3 days

earlier

Yes No

71

2a. VIGOROUS

PHYSICAL ACTIVITY Day

If yes, precisely describe activity/task, time and

duration. e.g. ran 10km at fast pace (5 mins per km)

10:00am - 50min.

The next questions are about

VIGOROUS PHYSICAL

ACTIVITY. This could be sports or

hobbies, paid or volunteer work,

work outside the home and

housework.

Examples of vigorous physical

activity include: running, rope

skipping, axe chopping, using heavy

tools, canoeing and truck driving.



involving VIGOROUS PHYSICAL

ACTIVITIES?



Now what about the day before…



OK now two days back… That was


day).

OK finally three days back… That

was the (restate their description of

the day)

Day of back

pain

Yes No

Day before

Yes No

2 days

earlier

Yes No

3 days

earlier

Yes No

72

2b. MODERATE



duration. e.g. Mowed the lawn. 11:00am -12:00 pm.


MODERATE PHYSICAL




housework.

Examples of moderate physical

activity include: leisure cycling,

fishing, general home repairs, music

playing, golf, surfing and painting.



involving MODERATE

PHYSICAL ACTIVITIES?








day).



the day).

Day of back

pain

Yes No

Day before

Yes No

2 days

earlier

Yes No

3 days

earlier

Yes No

73

3. SLIP, TRIP OR FALL [5] Day

If yes, precisely describe incident and time. e.g.

Descending stairs, missed bottom step and jarred back.

8:30am – one occasion.

Now I want you to think about SLIP,

TRIP OR FALL.


you have a slip, trip or fall? That


the day).







OK finally three days back….



Day of back

pain

Yes No

Day before

Yes No

2 days

earlier

Yes No

3 days

earlier

Yes No

74

4. CONSUMED ALCOHOL [6] Day

If yes, specify amount (refer to standard drink table at

the end of booklet), time and duration. E.g. 2x red wine

glasses (180ml). 8:20pm – 1h.


ALCOHOL CONSUMPTION.


you consume alcohol? That was the







day).



the day)

Day of back

pain

Yes No

Day before

Yes No

2 days

earlier

Yes No

3 days

earlier

Yes No

5. SEXUAL ACTIVITY [7] Day If yes, specify time. E.g. 11:00pm


SEXUAL ACTIVITY. So on the

day of your back pain did you

engage in sexual activity? That was


day).






day).



the day)

Day of back

pain

Yes No

Day before

Yes No

2 days

earlier

Yes No

3 days

earlier

Yes No

75

6. DISTRACTION [8] Day

If yes, specify time and duration, distraction and task.

e.g. Distracted by child crying while lifting a box from

car boot and it slipped from his/her hands. 8:30am –

one occasion.

Now I want you to think about being

DISTRACTED.

So on the day of your back pain were

you DISTRACTED for any reason

while engaged in a task or activity?








day).



the day)

Day of back

pain

Yes No

Day before

Yes No

2 days

earlier

Yes No

3 days

earlier

Yes No

7. FATIGUE OR TIREDNESS [9] Day

If yes, specify time and duration. e.g. Disrupted and

poor sleep the night before as youngest child kept

waking due to earache. 3:00am – 24h.


feeling FATIGUED or TIRED. So

on the day of your back pain did you

feel FATIGUED OR TIRED? That


the day).






day).



the day)

Day of back

pain

Yes No

Day before

Yes No

2 days

earlier

Yes No

3 days

earlier

Yes No

76

8. What do you think may have triggered your low back pain? (Record what the patient thinks may have

triggered his/her episode of back pain. eg. Bent down once to pick up newspaper from lawn. 7:00am -

immediately).

___________________________________________________________________________________________

____________________________________________________________________________________________

____________________________________________________________________________________________

____________________________________________________________________________________________

____________________________________________________________________________________________

So on the day of your back pain did you

do the activity described above? That

was the (restate their description of the

day).

Now what about the day before…. That


day).

OK now two days back… That was the


OK finally three days back… That was

the (restate their description of the day)

Day of back pain

Yes No

Day before

Yes No

2 days earlier

Yes No

3 days earlier

Yes No

77

Reference

1. Ware J, Sherbourne C: The MOS 36-item short-form health survey (SF-36). 1.

Conceptual framework and item selection. Medical Care 1992, 30:473-483.

2. Linton S, Hellsing A, Bergstrom G: Exercise for workers with musculoskeletal

pain: does enhancing compliance decrease pain? J Occup Med 1996, 6(3):177-190.

3. Armstrong T, Bauman A, Davies J: Physical activity patterns of Australian Adults.

In. Edited by Welfare AIoHa. Canberra; 2000.

4. Australian Safety Compensation Council: National code of practice for the

prevention of musculoskeletal disorders from performing manual tasks at work.

In. Canberra; 2007.

5. Verma S, Lombardi D, Chang W, Courtney T, Huang Y, Brennan M, Mittleman M,

Ware J, Perry M: Rushing, distraction, walking on contaminated floors and risk

of slipping in limited-service restaurants: a case--crossover study. Occupational &

Environmental Medicine 2010, 68(8):575-581.

6. Vinson DC, Mabe N, Leonard LL, Alexander J, Becker J, Boyer J, Moll J: Alcohol

and injury. A case-crossover study. Arch Fam Med 1995, 4(6):505-511.

7. Dahabreh IJ, Paulus JK, Dahabreh IJ, Paulus JK: Association of episodic physical

and sexual activity with triggering of acute cardiac events: systematic review and

meta-analysis. JAMA, 305(12):1225-1233.

8. Sorock G, Lombardi D, Peng D, Hauser R, Eisen E, Herrick R, Mittleman M: Glove

use and the relative risk of acute hand injury: a case-crossover study. Journal of

Occupational & Environmental Hygiene 2004, 1(3):182-190.

9. Chen S, Fong P, Lin S, Chang C, Chan C: A case-crossover study on transient risk

factors of work-related eye injuries. Occupational & Environmental Medicine

2009, 66(8):517-522.

78

Chapter Four

What triggers an episode of low back pain? A case-crossover study

Chapter Four is published as:

Steffens D, Ferreira ML, Latimer J, Ferreira PH, Koes BK, Blyth F, Li Q, Maher CG. What

triggers an episode of low back pain? A case-crossover study. Arthritis Care & Research.

2015; 67:403-410.

79


As co-authors of the paper “What triggers an episode of low back pain? A case-crossover

study”, we confirm that Daniel Steffens has made the following contributions:


Data collection







Fiona Blyth Date: 01.01.2015

Qiang Li Date: 01.01.2015


80

What Triggers an Episode of Acute Low BackPain? A Case–Crossover StudyDANIEL STEFFENS,1 MANUELA L. FERREIRA,2 JANE LATIMER,2 PAULO H. FERREIRA,2

BART W. KOES,3 FIONA BLYTH,2 QIANG LI,2 AND CHRISTOPHER G. MAHER2

Objective. To investigate a range of transient risk factors for an episode of sudden-onset, acute low back pain (LBP).Methods. This case–crossover study recruited 999 subjects with a new episode of acute LBP between October 2011 andNovember 2012 from 300 primary care clinics in Sydney, Australia. Each participant was asked to report exposure to 12putative triggers over the 96 hours preceding the onset of back pain. Conditional logistic regression was used to estimateodds ratios (ORs) expressing the magnitude of increased risk with exposure to each trigger.Results. Exposure to a range of physical and psychosocial triggers significantly increased the risk of a new onset of LBP;ORs ranged from 2.7 (moderate or vigorous physical activity) to 25.0 (distracted during an activity or task). Agemoderated the effect of exposure to heavy loads and sexual activity. The ORs for heavy loads for people ages 20, 40, or60 years were 13.6, 6.0, and 2.7, respectively. The risk of developing back pain was greatest between 7:00 AM and noon.Conclusion. Transient exposure to a number of modifiable physical and psychosocial triggers substantially increasesrisk for a new episode of LBP. Triggers previously evaluated in occupational injury studies, but never in LBP, have beenshown to significantly increase risk. These results aid our understanding of the causes of LBP and can inform thedevelopment of new prevention approaches.

INTRODUCTION

Back pain affects approximately 10% of the world’s pop-ulation at any point in time (1–3). When disease burden ismeasured by disability-adjusted life years, back pain is oneof the 10 leading causes of disease burden globally. Backpain is, however, unique among this list of 10 diseasesbecause there has been little or no progress in identifyingeffective prevention strategies (4–6).

Understanding what modifiable factors increase the riskof back pain is a crucial first step in prevention. Existingresearch has focused on factors that are not modifiable(e.g., age) or involve long-term exposure (e.g., smoking),

whereas the role of modifiable factors more proximal to theonset of back pain is yet to be investigated. Controllingexposure to these factors may be extremely important inpreventing back pain.

The case–crossover design provides an ideal method forquantifying the increased risk due to transient exposure totriggers (7,8). In this design a person acts as their owncontrol and hence the potential for between-person con-founding is reduced. This perfect matching is important inback pain research as it eliminates potential effects ofunmeasured confounders such as genetic and lifestyle in-fluences (9). The TRIGGERS study for low back pain aimedto investigate a number of transient physical and psycho-social risk factors for an episode of sudden-onset, acutelow back pain (LBP). Physical factors included heavyloads; awkward positioning; handling of objects far fromthe body; handling people or animals and unstable load-ing; a slip, trip, or fall; engagement in moderate or vigorousphysical activity; and sexual activity. Psychosocial factorsincluded alcohol consumption and being distracted andfatigued.

PATIENTS AND METHODS

Study design. The TRIGGERS study employed a case–crossover design to quantify the risk associated with tran-sient exposure to modifiable triggers for back pain. Trig-

Supported by the National Health and Medical ResearchCouncil of Australia.

1Daniel Steffens, BPT: The University of Sydney, Sydney,Australia, and Federal University of Minas Gerais, MinasGerais, Brazil; 2Manuela L. Ferreira, PhD, Jane Latimer,PhD, Paulo H. Ferreira, PhD, Fiona Blyth, PhD, Qiang Li,PhD, Christopher G. Maher, PhD: The George Institute forGlobal Health, The University of Sydney, Sydney, Australia;3Bart W. Koes, PhD: Erasmus Medical Center, Rotterdam,The Netherlands.

Address correspondence to Manuela L. Ferreira, PhD,The George Institute for Global Health, Sydney MedicalSchool, The University of Sydney, PO Box M201 MissendenRoad, Sydney, 2015, New South Wales, Australia. E-mail:[email protected].

Submitted for publication August 21, 2014; accepted inrevised form December 9, 2014.

Arthritis Care & ResearchVol. 67, No. 3, March 2015, pp 403–410DOI 10.1002/acr.22533© 2015, American College of Rheumatology

ORIGINAL ARTICLE

403

81

gers from the list of hazardous tasks provided in a nationalcode of practice were included (10). Additionally a num-ber of factors that had been previously identified as trig-gers in occupational injury studies (11–14), but never eval-uated in the area of back pain, were included. Theexposure to each trigger during the 2 hours preceding theonset of back pain (case window) was compared to expo-sure in two 2-hour periods ending 24 and 48 hours beforethe onset of back pain (control windows). The study wasapproved by the Human Research Ethics Committee of theUniversity of Sydney (protocol number 05-2011/13742). Adetailed protocol has been previously published (15).

Participants. A total of 999 consecutive patients, age�18 years and with a new episode of acute back pain, wererecruited from 300 primary care clinics in New SouthWales, Australia between October 2011 and November2012. A new episode of back pain was defined as a primarycomplaint of pain between the 12th rib and the buttockcrease, with or without leg pain, causing the patient toseek health care or take medication and preceded by aperiod of at least 1 month without back pain (16). Patientsneeded to present to primary care within 7 days from painonset and report pain of at least moderate intensity inthe first 24 hours of the current episode (measured usingitem 7 of the Short Form 36 questionnaire). This inclusionmeans that we did not study patients with an insidiousonset, a less common presentation for nonspecific backpain that would be less suited to study with a case–crossover design (17). Patients were excluded from thestudy if they presented with known or suspected seriousspinal pathology (e.g., metastatic, inflammatory, or infec-tive diseases of the spine). All participants gave writteninformed consent for participation.

Study interview. Participants were interviewed byphone within 7 days following referral to the study.Trained research staff used an interview script to collectsociodemographic and clinical characteristics of the backpain episode as well as data on exposure to a variety ofpossible triggers. The interview script was piloted on 20

subjects with back pain and adjustments made to improveclarity and participant recall.

During the interview, participants were asked to identifythe date and time of pain onset with the assistance ofrecommended recall aids such as a diary, calendar, and/orsmartphone. Each participant was then asked to reportexposure, including its time and duration, to each of the 12putative triggers in the 96 hours preceding the onset ofback pain. For example, for questions about manual tasksinvolving a heavy load would be as follows: so on the dayof your back pain did you engage in any manual tasksinvolving a heavy load? That was the . . . (the interviewerwould restate the participant’s description of the day, i.e.,that was the quite warm day you went to church). Nowwhat about the day before . . . (the interviewer would re-state the description of that day, i.e., the windy day whenyou did your weekly shopping). What about two daysback. That was the . . . (the interviewer would restate thedescription of that day, i.e., the day you visited your par-ents and it rained all day). Participants, clinicians, andinterviewers were blinded to the time and length of thepredetermined case and control windows.

Physical triggers included manual tasks (heavy loads,awkward positioning, handling of objects far from thebody, and handling people or animals and unstable load-ing); a slip, trip, or fall; engagement in moderate or vigor-ous physical activity; and sexual activity. Physical activi-ties were coded as moderate or vigorous physical activityconsidering their energy cost (18). Psychosocial triggersincluded alcohol consumption and being distracted or fa-tigued. Recruiting clinicians were not aware of the specifictriggers evaluated in the study. Although data were ob-tained for exposure to the 12 putative triggers over the 96hours prior to back pain onset, the primary analysis onlyused data for the 2-hour period immediately preceding theback pain onset and for the two 2-hour periods ending 24and 48 hours before the pain onset.

Participants were also questioned regarding their habit-ual physical activity. This was assessed using the ActiveAustralia questionnaire, which estimates the total numberof hours of light, moderate, and vigorous physical activityperformed by the participant in the past week (19). For thepurpose of this study, the questionnaire was modified toinclude the recall period of interest, i.e., the week beforethe onset of back pain. Supplementary Appendix A, avail-able in the online version of this article at http://onlinelibrary.wiley.com/doi/10.1002/acr.22533/abstract, pre-sents the study questionnaire.

Statistical analysis. The frequency of exposure to eachtrigger was calculated for the case window (2 hours priorto onset of back pain) and 2 control windows (24–26 hoursand 48–50 hours prior to onset of back pain, respectively).A frequency distribution graph of pain onset by time ofday (in hours) was calculated. Conditional logistic regres-sion models were constructed to quantify the risk of backpain onset associated with each trigger, where each par-ticipant represented a matched set of data for case andcontrol exposures (20). Odds ratios (ORs) and 95% confi-dence intervals (95% CIs) were derived comparing expo-

Significance & Innovations● Back pain is the leading cause of disability glob-

ally, yet there has been little or no progress inidentifying effective prevention strategies.

● To date, no studies have examined the role ofexposure to transient risk factors in triggering anepisode of acute low back pain.

● The results of this study demonstrate for the firsttime that brief exposure to a range of physical andpsychosocial factors can considerably increase therisk of an episode of acute back pain.

● These results will have significant clinical andpolicy implications for the control of a disease thatis a major problem worldwide.

404 Steffens et al

82

sure in the case window with each of 2 control windows.Conditional logistic regression was also used to assessvalidity of the control windows by comparing their expo-sure data. Secondary analyses evaluated interaction be-tween exposure to triggers and habitual physical activity,age, body mass index (BMI), number of previous LBPepisodes, depression, and anxiety scores.

It is plausible that physical and psychosocial factorscould cause an episode of back pain that does not becomeapparent in the 2 hours after the participant was exposed.Therefore, sensitivity analyses were conducted using caseand control windows of 4- and 6-hour duration. Sensitiv-ity analyses using case and control windows of 1-hourduration were also performed. STATA 12 software wasused for all analyses.

Sample size. The study was designed to be adequatelypowered for the primary analysis, which involves estima-tion of the risk associated with transient exposure to thedifferent types of triggers by comparing exposures in thecase window to the first control window. We calculatedthe sample size necessary for a paired case–control studyusing the procedures described by Dupont (21). Samplesize was estimated using procedures for a paired case–control design (21). With alpha set at 0.05, a sample of1,000 cases would provide an 80% probability of detectingan OR of 1.5 or greater across the plausible range of expo-sure prevalence in control windows (0.2–0.8) and theplausible range of correlations between exposure in caseand control windows (0.0–0.5).

RESULTS

Primary care clinicians referred 1,639 patients with a newepisode of back pain, with 999 being interviewed andcontributing data to the study (Figure 1).

Patterns of pain onset. The mean � SD duration of theepisode was 4.9 � 2.7 days, with a mean � SD timebetween pain onset and presentation to primary care of2.0 � 2.1 days, and 1.9 � 2.0 days from presentation tointerview (Table 1). Approximately half the participants(49.5%) reported having severe pain in the first 24 hours of

Figure 1. Study recruitment flow chart. LBP � low back pain.

Table 1. Characteristics of the participants (n � 999)*

Characteristics Value

Age, years 45.3 � 13.4Male sex 541 (54.2)Height, cm 172.4 � 10.4Weight, kg 78.9 � 18.1†Body mass index, kg/m2‡ 26.4 � 5.2†Duration of current episode, days 4.9 � 2.7Number of previous episodes 5.9 � 14.0Days to seek care 3.0 � 2.1Days from presentation to health care and

interview2.0 � 2.0

Days of reduced activity 2.3 � 2.2Pain scores (0–10) 5.3 � 2.1Currently taking medication 452 (45.3)Currently employed 836 (83.7)Workers compensation 89 (8.9)If in paid employment, what is done for a

livingNot employed 163 (16.3)Clerical/administrative worker 103 (10.3)Community/personal service worker 47 (4.7)Laborer 30 (3.0)Machinery operator/driver 27 (2.7)Manager 159 (15.9)Professional 341 (34.1)Sales worker 52 (5.2)Technician/trade worker 77 (7.7)

Pain location§Upper back 59 (5.9)Lower back 999 (100)Left thigh (back) 97 (9.7)Left leg (back) 44 (4.40)Right thigh (back) 107 (10.7)Right leg (back) 48 (4.8)Right thigh (front) 29 (2.9)Right leg (front) 11 (1.1)Left thigh (front) 27 (2.7)Left leg (front) 8 (0.8)

Pain severity in first 24 hoursModerate 373 (37.3)Severe 494 (49.5)Very severe 132 (13.2)

Pain interfering with work in first 24 hoursNot at all 21 (2.1)A little bit 101 (10.1)Moderately 250 (25.0)Quite a bit 389 (38.9)Extremely 238 (23.8)

Habitual physical activity in last week¶Sedentary 542 (54.3)Insufficient activity 164 (16.4)Sufficient activity 293 (29.3)

Habitual physical activity during weekbefore

Sedentary 360 (36.0)Insufficient activity 174 (17.4)Sufficient activity 465 (46.6)

Tense/anxious scores 4.0 � 2.6Depression scores 2.7 � 2.7

* Values are the number (percentage) or the mean � SD.† N � 998.‡ Body mass index � weight in kilograms divided by the square ofthe height in meters.§ Pain location was assessed using a pain mannequin provided tothe participant by the referring clinician.¶ Habitual physical activity: moderate activity time � (2 � vigorousactivity time). Sedentary (zero), insufficient activity (�1 to �149),and sufficient activity (�150).

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the current episode, and 87.8% reported that pain inter-fered at least moderately with daily activities. Morningswere the most frequent time of day for back pain onset,with 35.2% of participants (n � 352) reporting pain onsetbetween 7:00 AM and 10:00 AM (Figure 2). Only 3.7% ofparticipants (n � 37) reported pain onset between mid-night and 5:00 AM, with a large increase in reports from6:00 AM.

Exposure to potential triggers. Exposure to all physicaltriggers was more frequent in the case window than in the

2 control windows (Table 2). The highest exposure in thecase window was to manual tasks involving an awkwardposture (27.4% of case windows; 7% for first control win-dow and 5.4% for second control window), followed bymanual tasks involving heavy loads (17.9% in case win-dows; 6.4% and 5.9% in the first and second controlwindows, respectively). A total of 37 participants reportedbeing exposed to a slip, trip, or fall in the 2 hours beforepain onset, compared to only 1 participant in the firstcontrol window and none in the second control window.This suggests a strong association between this trigger and

Figure 2. Frequency of back pain onset by time of day for 999 participants.Panel shows the percentage of episodes that commenced in each 1-hour timeepoch across the day.

Table 2. Exposure frequency and ORs for each trigger: primary analysis (2-hour window)*

Triggers

Case window(0–2 hours)

no. (%)

First control window(24–26 hours)

no. (%)

Second control window(48–50 hours)

no. (%) OR (95% CI)† P

Physical factorsManual tasks involving…

Heavy loads 179 (17.9) 64 (6.4) 59 (5.9) 5.0 (3.3–7.4) � 0.001Awkward posture 274 (27.4) 70 (7.0) 54 (5.4) 8.0 (5.5–11.8) � 0.001Objects not close to the body 40 (4.0) 14 (1.4) 10 (1.0) 6.2 (2.4–15.9) � 0.001People or animals 86 (8.6) 62 (6.2) 63 (6.3) 5.8 (2.3–15.0) � 0.001Unstable, unbalanced,

difficult to grasp52 (5.2) 19 (1.9) 13 (1.3) 5.1 (2.4–10.9) � 0.001

Moderate or vigorous physicalactivity

225 (22.5) 129 (12.9) 112 (11.2) 2.7 (2.0–3.6) � 0.001

Vigorous physical activity only 105 (10.5) 44 (4.4) 38 (3.8) 3.9 (2.4–6.3) � 0.001Slip/trip/fall‡ 37 (3.7) 1 (0.1) 0 (0.0) – –Sexual activity 8 (0.8) 11 (1.1) 11 (1.1) 0.7 (0.3–1.8) 0.49

Psychosocial factorsConsumption of alcohol 13 (1.3) 9 (0.9) 12 (1.2) 1.5 (0.6–3.7) 0.37Distracted during an activity

or task30 (3.0) 6 (0.6) 8 (0.8) 25.0 (3.4–184.5) 0.002

Fatigued/tired 118 (11.8) 69 (6.9) 60 (6.0) 3.7 (2.2–6.3) � 0.001

* Results of the primary analyses based on case and control windows of 2 hours duration. OR � odds ratio; 95% CI � 95% confidence interval.† For the primary analysis, ORs and 95% CIs were derived by comparing exposure in the case window (0–2 hours) to exposure in the first controlwindow (24–26 hours).‡ Due to small frequencies of exposure in the control windows, this trigger could not be included in the conditional logistic regression analyses.

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onset of back pain; however, exposure frequencies werevery small in the control windows and slip, trip, or fallcould not be sensibly included in the regression analyses.

Exposure frequency for being fatigued and tired washigher in the case window (11.8%) than control windows(6.90% and 6.00% in the first and second control win-dows, respectively). However, for sexual activity and al-cohol consumption, exposure frequency was similaracross case and control windows (Table 2).

Association of exposure and risk of back pain. Allphysical triggers included in the analysis were stronglyassociated with an increased risk of back pain (Table 2).Exposure to manual tasks involving awkward positioningwas associated with 8.0 (95% CI 5.5–11.8) times greaterodds of the onset of back pain. Likewise, the OR associatedwith exposure to manual tasks involving objects not closeto the body was 6.2 (95% CI 2.4–16.0), 5.80 (95% CI2.3–15.0) for manual tasks involving people or animals,

and 5.1 (95% CI 2.4–10.9) for manual tasks involvingunstable or unbalanced objects. Being exposed to physicalactivity of at least moderate intensity (i.e., participantsreporting being exposed to either moderate or vigorousphysical activity) increased the odds of developing backpain in the following 2 hours by 2.7 (95% CI 2.0–3.6)when compared to no exposure to physical activity. Theodds increased further when participants were exposed tovigorous physical activity (i.e., only participants reportingbeing exposed to vigorous physical activity) compared tono physical activity (OR 3.9, 95% CI 2.4–6.3).

Among the psychosocial triggers, being distracted dur-ing a task or activity (OR 25.0, 95% CI 3.4–184.5) orfatigued (OR 3.7, 95% CI 2.2–6.3) increased significantlythe odds of a new onset of back pain, but alcohol consump-tion and sexual activity showed no association with onsetof back pain.

No significant change in OR estimates was observedwhen window duration was increased to 4 hours (Supple-

Table 3. Influence of time of onset on risk: ORs for back pain that developed in the morning versus later in the day*

Triggers

Time of onset, 7 AM to 12 PM

(n � 441)Time of onset, 1 PM to 6 AM

(n � 558) Interactionanalysis,

P†OR (95% CI) P OR (95% CI) P

Physical factorsManual tasks involving

Heavy loads 5.3 (2.70–10.4) � 0.0001 4.8 (2.9–7.9) � 0.0001 0.813Awkward posture 13.4 (6.5–27.4) � 0.0001 6.0 (3.8–9.5) � 0.0001 0.066Objects not close to the body 7.5 (1.7–32.8) 0.007 5.3 (1.6–18.3) 0.008 0.728People/animals 7.0 (1.59–30.8) 0.01 5.0 (1.5–17.3) 0.011 0.733Unstable/unbalanced/difficult to grasp 9.5 (2.2–40.8) 0.002 3.7 (1.5–9.0) 0.005 0.276

Moderate or vigorous physical activity 1.9 (1.2–3.0) 0.008 3.3 (2.2–5.0) � 0.0001 0.072Vigorous physical activity 2.5 (1.2–5.2) 0.014 5.2 (2.7–9.9) � 0.0001 0.144Slip/trip/fall‡Sexual activity 1.0 (0.4–2.9) 1.0 0.3 (0.0–2.2) 0.215 0.263

Psychosocial factorsConsumption of alcohol – – 1.5 (0.6–3.7) 0.374 –Distracted during an activity or task 12.0 (1.6–92.3) 0.017Fatigued/tired 4.5 (1.9–10.9) 0.001 3.3 (1.8–6.4) � 0.0001 0.591

* Results of post hoc analyses based on case and control windows of 2-hours’ duration. OR � odds ratio; 95% CI � 95% confidence interval.† Interaction test between risk factors (7:00 AM to 12:00 PM and 1:00 PM to 6:00 AM).‡ Due to small frequencies of exposure, this trigger could not be included in the conditional logistic regression analyses.

Table 4. ORs for combined triggers: secondary analysis (2-hour window)*

Combined Triggers

Case window(0–2 hours)

no. (%)

First control window(24–26 hours)

no. (%)

Second control window(48–50 hours)

no. (%)OR

(95% CI)† P

Heavy loads � awkward posture 89 (8.9) 22 (2.2) 11 (1.1) 6.2 (3.4–11.1) � 0.0001Heavy loads � unstable/unbalanced/

difficult to grasp43 (4.3) 15 (1.5) 8 (0.8) 5.0 (2.2–11.3) � 0.0001

Heavy loads � fatigued 23 (2.3) 6 (0.6) 3 (0.3) 5.3 (1.8–15.3) 0.002Heavy loads � object not close to

body25 (2.5) 12 (1.2) 6 (0.6) 3.2 (1.3–7.9) 0.014

Moderate or vigorous physicalactivity � fatigued

24 (2.4) 4 (0.4) 5 (0.5) 7.7 (2.3–25.5) 0.001

* OR � odds ratio; 95% CI � 95% confidence interval.† ORs describe the increase in odds of an episode of low back pain when exposed to the combined trigger compared to not being exposed to thecombined trigger.


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mentary Table 1, available in the online version of thisarticle at http://onlinelibrary.wiley.com/doi/10.1002/acr.22533/abstract) or 6 hours (Supplementary Table 2, avail-able in the online version of this article at http://onlinelibrary.wiley.com/doi/10.1002/acr.22533/abstract). TheOR estimates observed when window duration was de-creased to 1 hour (Supplementary Table 3, available in theonline version of this article at http://onlinelibrary.wiley.com/doi/10.1002/acr.22533/abstract) were similar to theprimary analysis (window duration of 2 hours) (Table 2).

Interactions. No interaction was observed between ex-posure to any trigger and habitual participation in physicalactivity, BMI, number of previous LBP episodes, depres-sion, and anxiety score with P values greater than 0.05 forall triggers (Supplementary Table 4, available in the onlineversion of this article at http://onlinelibrary.wiley.com/doi/10.1002/acr.22533/abstract). However, age moderatedthe effect of exposure to manual tasks involving heavyloads (P � 0.01) and sexual activity (P � 0.04). To illus-trate the moderating effect of age on exposure to these 2triggers, we used the coefficients from the regression mod-els to calculate the ORs for a subject age 20, 40, or 60 years.For manual tasks involving heavy loads these were asfollows: at 20 years: OR 13.6, 95% CI 5.4–34.5, P � 0.01;at 40 years: OR 6.0, 95% CI 3.8–9.5, P � 0.01; and at 60years: OR 2.7, 95% CI 1.5–4.7, P � 0.01). For sexualactivity these were as follows: at 20 years: OR 0.05, 95% CI0.03–0.97, P � 0.04; at 40 years: OR 0.41, 95% CI 0.12–1.43, P � 0.16; and at 60 years: OR 3.21, 95% CI 0.57–18.22, P � 0.19).

Given the unexpected diurnal pattern of pain onsetobserved in our study, with more episodes commencingin the morning, exploratory post hoc analyses were con-ducted to evaluate if the back was more vulnerable totriggers in the morning. We evaluated the risk associatedwith being exposed to triggers in the period between7:00 AM and 12:00 PM to that between 1:00 PM and 6:00 AM.While there was no statistically significant interaction be-tween time of exposure and risk of developing back pain,when compared to the afternoon or night, exposure toawkward posture (OR 13.4, 95% CI 6.5–27.4) and manualtasks involving unstable loading (OR 9.5, 95% CI 2.2–40.8)in the morning was more strongly associated with risk ofback pain onset (Table 3). Unfortunately our study lackedsufficient power to resolve this issue.

Multiple triggers. A theory-driven approach was ad-opted to select combinations of triggers that would in-crease the risk of back pain onset. Five combinationswere chosen by consensus among investigators as follows:1) manual tasks involving heavy loads and awkward pos-ture; 2) manual tasks involving heavy loads and loads thatare unstable, unbalanced, or difficult to grasp; 3) manualtasks involving heavy loads and being fatigued; 4) manualtasks involving heavy loads and objects far from the body;and 5) being engaged in moderate or vigorous physicalactivity and feeling fatigued (Table 4). These analyses werenot prespecified in the study protocol. Manual tasks in-volving heavy loads associated with awkward posture in-

creased the odds of developing back pain by 6.2 (95% CI3.4–11.1, P � 0.00001) and by 5.3 (95% CI 1.8–15.3, P �0.002) if associated with feeling fatigued when comparedto no exposure. Similarly, engaging in physical activityseems to increase further the risk of back pain if associatedwith feeling fatigued or tired (OR 7.7, 95% CI 2.3–25.5,P � 0.001).

DISCUSSION

To date, back pain risk studies have only examined long-term exposure to factors such as smoking and inactivity(22). Our study adds to the knowledge of risk of back painby demonstrating for the first time that brief exposure to arange of modifiable physical and psychosocial factors in-creases the risk of an episode of back pain. The ORs for thetriggers we evaluated ranged from 2.7 to 25.0, confirmingthat short-term exposure may substantially increase risk ofback pain. Older age decreased the risk associated withmanual tasks involving heavy loads and increased the riskin those exposed to sexual activity. Habitual physical ac-tivity, age, BMI, previous number of LBP episodes, depres-sion, and anxiety scores did not significantly change therisk associated with exposure to the other investigatedtriggers. Notably, we also demonstrated that the onset ofback pain is not evenly distributed across the day, withmornings being the most frequent time of day for back painonset.

A major strength of our study was the large representa-tive sample of patients with a moderate to severe episodeof back pain recruited at inception. Moreover, the self-matching in case–crossover designs addresses some of theimportant limitations of previous risk studies in the backpain field (23,24). Self-matching eliminates potential ef-fects of unmeasured confounders, such as genetic andlifestyle factors, and minimizes selection bias (9). A poten-tial limitation of case–crossover studies is the potential forrecall bias, especially if the recall period is long; however,in our study the mean time between episode onset andinterview was only 5 days. Further, in an attempt to max-imize recall, participants were asked to link the day ofonset of back pain and each of the 3 previous control daysto significant events using a calendar and/or personal di-ary. If participants were more likely to remember what hadhappened during the case window than in the controlwindows (i.e., differential recall bias), the effect of a triggerwould be overestimated. To minimize this potential prob-lem research assistants and participants were blinded tothe case and control windows. We also acknowledge thatfor some people recall may have been difficult, so ourinterview script asked participants to refer to their diary/smartphone and to nominate key aspects of each day.Participants were also blinded to the time and length of thecase and control windows and were asked to describe theirengagement in each trigger over a period of 96 hours.These strategies have been used successfully in othercase–crossover studies and suggest that participants are asable to recall data on the preceding 2 days as they are onthe day of the event (25). Furthermore, the analysis of thestudy did not control for time-variant confounders beyond

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the triggers included in the study. We acknowledge, there-fore, that additional time-variant confounders may haveinfluenced our study findings.

A recent systematic review has identified multiple psy-chosocial and physically related risk factors for LBP (26).No consistent risk factor emerged as predictive of first-timeLBP, although prior LBP was a consistent predictor offuture incident LBP. However, many of the risk factorsinvestigated are not robust or replicable, and many are notmodifiable. Our results demonstrate that the onset of backpain may be triggered by brief exposure to physical andpsychological factors. Past research has linked long-termexposure to physical risk factors, such as heavy loads andawkward posture, and future occurrence of back pain withthe accumulation of exposure over time holding strongerassociations (23). Our results provide the first accurateestimates to confirm that even brief exposure to thesephysical factors may trigger moderate to severe back pain.The importance of psychosocial factors has also been high-lighted as our results have identified that transient expo-sure to stress and fatigue triples the odds of developingimmediate back pain, whereas distraction increases theodds by a factor of 25.

Results from our interaction analysis suggested that agemoderates the effect of exposure to manual tasks involvingheavy loads. Interestingly, the odds associated with man-ual tasks involving heavy loads at age 60 years is morethan 5 times smaller than at age 20 years. While previousstudies have reported the association between long-termexposure to heavy loads and LBP (23), this is the first studythat demonstrates a decrease in risk with age. One poten-tial reason for this may be that older people have learnedto lift correctly or are more careful when handling heavyloads. Future research is required to evaluate this hypoth-esis.

There is little published information about the time ofonset of back pain. Biomechanists have theorized that therisk of back pain may be higher in the morning as inter-vertebral discs imbibe fluid overnight, leaving them moresusceptible to stresses when loaded (27,28). Sprains andstrains (an injury category that includes back pain) havebeen previously associated with a similar diurnal patternto our study with �40% of sprains and strains occurringfrom 8:00 AM to 11:00 AM (29). The strong diurnal patternfor back pain onset would suggest that the morning may bea key time to intervene in order to prevent back pain. Thisapproach was adopted in a sham controlled trial (30) thatshowed that advising patients with persistent LBP to re-strict lumbar flexion in the morning was effective in re-ducing pain. Unfortunately, our post hoc analyses pro-vided imprecise estimates of the effect of time of exposureon the triggers evaluated in the study. Nonetheless theOR point estimates for morning exposure (i.e., 7:00 AM to12:00 PM) to manual tasks involving awkward posture andthose involving unstable, unbalanced, and difficult tograsp objects were meaningfully different to the point es-timates for exposure at other times. While larger studiesare still clearly required, our study provides preliminaryevidence that both the nature of the trigger and the time ofday of exposure to the trigger may influence the risk ofdeveloping back pain.

The challenge for future research is to develop and eval-uate prevention programs that aim to reduce exposure tothe triggers identified in this study by thoughtfully con-sidering each trigger. Exposure to triggers such as manualtasks involving heavy loads could be completely avoidedby redesigning the workplace so workers are no longerrequired to lift heavy loads. Exposure to other triggerscould be reduced by education, for example, throughpopulation-based public health messaging or onsite train-ing of workers. Some triggers such as slips, trips, and fallsare probably more difficult to avoid, but we would notethat there are successful falls prevention strategies di-rected at the elderly, suggesting that even these triggers arepotentially avoidable. It may not be sensible to aim toavoid the trigger “moderate or vigorous physical activity”because, while transient exposure increases the risk ofLBP, long-term exposure has many health benefits againstmany chronic diseases.

We acknowledge that changing human behavior is farfrom simple; however, the burden of back pain around theglobe does provide a compelling case that somethingshould be done. For example, the burden of disease dueto road traffic injury is far less than that for back pain,yet many countries devote considerable resources to con-trolling behaviors that increase the risk of road crashes.For example, mobile phone use has been shown in case–crossover studies to increase the risk for road crashes,which has led to media campaigns to change driver be-havior.

An important unanswered question from our study iswhether long-term exposure to risk factors, such assmoking and driving, moderate the risk associated withtransient exposure to the triggers we studied. We alsoacknowledge that our secondary analyses evaluatingwhether attributes of the person (such as BMI and habitualphysical activity) moderate the risk of developing lowback pain, were underpowered, and we would encouragelarger studies to evaluate this important issue. Future re-search directed at determining how best to modify thetriggers identified in this study, and whether incorporatingthis knowledge into prevention programs leads to reducedepisodes of LBP, should be also conducted. Moreover, wedid not collect data on the place of occurrence of LBP.Future studies could investigate whether the trigger stud-ied occurred in the work place, during sport, or at home.

Our results have significant clinical and policy implica-tions for the control of a disease that is a major problemglobally. We offer robust estimates for the increase in riskof back pain following exposure to modifiable physicaland psychosocial triggers. Future research should evaluatethe success of programs that modify the triggers identifiedin this study in preventing episodes of back pain.

AUTHOR CONTRIBUTIONSAll authors were involved in drafting the article or revising

it critically for important intellectual content, and all authorsapproved the final version to be submitted for publication.Dr. M. Ferreira had full access to all of the data in the study andtakes responsibility for the integrity of the data and the accuracyof the data analysis.Study conception and design. Steffens, M. Ferreira, Latimer,P. Ferreira, Koes, Blyth, Li, Maher.


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Acquisition of data. Steffens, M. Ferreira, Latimer, Blyth, Li,Maher.Analysis and interpretation of data. Steffens, M. Ferreira,Latimer, P. Ferreira, Koes, Blyth, Li, Maher.

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30. Snook S, Webster B, McGorry R, Fogleman M, McCann K. Thereduction of chronic nonspecific low back pain through thecontrol of early morning lumbar flexion: a randomized con-trolled trial. Spine (Phila Pa 1976) 1998;23:2601–7.

31. Ware J, Sherbourne C. The MOS 36-item short-form healthsurvey (SF-36). 1. Conceptual framework and item selection.Med Care 1992;30:473–83.

32. Linton S, Hellsing A, Bergstrom G. Exercise for workers withmusculoskeletal pain: does enhancing compliance decreasepain? J Occup Med 1996;6:177–90.

33. Dahabreh IJ, Paulus JK. Association of episodic physical andsexual activity with triggering of acute cardiac events: system-atic review and meta-analysis. JAMA 2011;305:1225–33.

410 Steffens et al

88

Ap

pen

dix

Ta

ble

1.

Exp

osu

re f

req

uen

cy a

nd

od

ds

rati

os

for

each

tri

gger

- s

en

siti

vit

y a

nal

ysi

s (4

ho

ur

win

do

w)

Tri

gg

ers

Ca

se W

ind

ow

(0-4

ho

urs

), N

o. (%

)

Fir

st C

on

tro

l W

ind

ow

(2

4-

28

ho

urs

), N

o.

(%)

Sec

on

d C

on

tro

l W

ind

ow

(48

-52

ho

urs

), N

o.

(%)

Od

ds

Ra

tio

(9

5%

CI)

P

Ph

ysi

cal

fact

ors

M

anual

task

s in

vo

lvin

g

Hea

vy l

oad

s 2

02

(2

0.2

) 7

9 (

7.9

) 6

7 (

6.7

) 5

.0 (

3.4

to 7

.3)

<0

.00

01

Aw

kw

ard

po

sture

2

90

(2

9.0

) 8

2 (

8.2

) 6

1 (

6.1

) 7

.3 (

5.1

to 1

0.5

) <

0.0

001

Obje

cts

no

t cl

ose

to

the

bo

dy

4

4 (

4.4

) 1

9 (

1.9

) 1

3 (

1.3

) 4

.1 (

1.9

to 8

.9)

<0

.00

01

Liv

e p

eop

le/

anim

als

92

(9

.2)

71

(7.1

) 6

5 (

6.5

) 3

.1 (

1.5

to 6

.3)

0.0

02

Unst

able

/ u

nb

alan

ce/

dif

ficult

to

gra

sp o

r ho

ld

61

(6

.1)

22

(2.2

) 1

6 (

1.6

) 4

.9 (

2.5

to 9

.7)

<0

.00

01

M

od

erat

e o

r vig

oro

us

ph

ysi

cal

act

ivit

y

25

0 (

25

.0)

16

0 (

16

.0)

14

2 (

14

.2)

2.2

(1

.7 t

o 2

.9)

<0

.00

01

V

igo

rous

ph

ysi

cal

acti

vit

y o

nly

1

13

(1

1.3

) 5

9 (

5.9

) 4

7 (

4.7

) 2

.6 (

1.7

to 3

.8)

<0

.00

01

S

lip

/ tr

ip/

fall

*

38

(3

.8)

1 (

0.1

) 0

(0

.0)

--

--

S

exual

act

ivit

y

11

(1

.1)

19

(1.9

) 1

3 (

1.3

) 0

.6 (

0.3

to 1

.2)

0.1

36

Psy

cho

soci

al f

acto

rs

C

onsu

mp

tio

n o

f al

coho

l 1

9 (

1.9

) 1

5 (

1.5

) 1

6 (

1.6

) 1

.3 (

0.6

to 2

.8)

0.4

51

D

istr

acte

d d

uri

ng a

n a

ctiv

ity o

r ta

sk

31

(3

.1)

6 (

0.6

) 9

(0

.9)

26

.0 (

3.5

to

19

1.6

) 0

.00

1

F

atig

ued

/ ti

red

1

32

(1

3.2

) 7

8 (

7.8

) 6

9 (

6.9

) 3

.8 (

2.3

to 6

.4)

<0

.00

01

Res

ult

s o

f se

nsi

tivit

y a

nal

yse

s b

ased

on c

ase

and

co

ntr

ol

win

do

ws

of

4 h

ours

dura

tio

n.

89

*D

ue

to s

mal

l fr

equen

cies

of

exp

osu

re i

n t

he

contr

ol

win

do

ws,

this

tri

gger

co

uld

no

t b

e in

clud

ed i

n c

ond

itio

nal

lo

gis

tic

regre

ssio

n a

nal

yse

s.

90

Ap

pen

dix

Ta

ble

2.

Exp

osu

re f

req

uen

cy a

nd

od

ds

rati

os

for

each

tri

gger

s -

sensi

tivit

y a

nal

ysi

s (6

ho

ur

win

do

w)

Tri

gg

ers

Ca

se W

ind

ow

(0-4

ho

urs

), N

o. (%

)

Fir

st C

on

tro

l W

ind

ow

(2

4-2

8

ho

urs

), N

o.

(%)

Sec

on

d C

on

tro

l W

ind

ow

(48

-52

ho

urs

), N

o.

(%)

Od

ds

Ra

tio

(9

5%

CI)

P

Ph

ysi

cal

fact

ors

M

anual

task

s in

vo

lvin

g

Hea

vy l

oad

s 2

10

(2

1.0

) 8

8 (

8.8

) 7

2 (

7.2

) 4

.4 (

3.1

to 6

.3)

<0

.00

01

Aw

kw

ard

po

sture

3

01

(3

0.1

) 8

6 (

8.6

) 6

3 (

6.3

) 7

.1 (

5.0

to 1

0.2

) <

0.0

001

Obje

cts

no

t cl

ose

to

the

bo

dy

4

4 (

4.4

) 2

1 (

2.1

) 1

3 (

1.3

) 3

.3 (

1.6

to 6

.7)

0.0

01

Liv

e p

eop

le/

anim

als

97

(9.7

) 7

4 (

7.4

) 7

2 (

7.2

) 3

.3 (

1.6

to 6

.7)

0.0

01

Unst

able

/ u

nb

alan

ce/

dif

ficult

to

gra

sp o

r ho

ld

64

(6.4

) 2

5 (

2.5

) 1

6 (

1.6

) 4

.0 (

2.2

to 7

.4)

<0

.00

01

M

od

erat

e o

r vig

oro

us

ph

ysi

cal

act

ivit

y

26

3 (

26

.3)

17

3 (

17

.3)

15

3 (

15

.3)

2.1

(1

.6 t

o 2

.8)

<0

.00

01

V

igo

rous

ph

ysi

cal

acti

vit

y o

nly

1

19

(1

1.9

) 6

4 (

6.4

) 5

3 (

5.3

) 2

.5 (

1.7

to 3

.7)

<0

.00

01

S

lip

/ tr

ip/

fall

*

38

(3.8

) 1

(0

.1)

0 (

0.0

) --

--

S

exual

act

ivit

y

13

(1.3

) 2

2 (

2.2

) 1

9 (

1.9

) 0

.6 (

0.3

to 1

.2)

0.1

22

Psy

cho

soci

al f

acto

rs

C

onsu

mp

tio

n o

f al

coho

l 2

2 (

2.2

) 2

0 (

2.0

) 2

1 (

2.1

) 1

.1 (

0.6

to 2

.3)

0.7

24

D

istr

acte

d d

uri

ng a

n a

ctiv

ity o

r ta

sk

31

(3.1

) 6

(0

.6)

9 (

0.9

) 2

6.0

(3

.5 t

o 1

91

.6)

0.0

01

F

atig

ued

/ ti

red

1

38

(1

3.8

) 8

7 (

8.7

) 7

5 (

7.5

) 3

.2 (

2.0

to 5

.1)

<0

.00

01

91

Res

ult

s o

f se

nsi

tivit

y a

nal

yse

s b

ased

on c

ase

and

co

ntr

ol

win

do

ws

of

6 h

ours

dura

tio

n.

*D

ue

to s

mal

l fr

equen

cies

of

exp

osu

re i

n t

he

contr

ol

win

do

ws,

this

tri

gger

co

uld

no

t b

e i

ncl

ud

ed i

n c

ond

itio

nal

lo

gis

tic

regre

ssio

n a

nal

yse

s.

92

Ap

pen

dix

Ta

ble

3.

Inte

ract

ion a

nal

ysi

s b

etw

een b

aseli

ne

vari

able

s an

d p

hysi

cal

and

psy

cho

logic

al f

acto

rs

Ph

ysic

al

fact

ors

Ha

bit

ua

l p

hy

sica

l

act

ivit

y*

Ag

e*

BM

I*

Pre

vio

us

epis

od

es*

D

epre

ssio

n*

A

nxie

ty*

OR

(9

5%

CI)

P

O

R (

95

% C

I)

P

OR

(9

5%

CI)

P

O

R (

95

% C

I)

P

OR

(9

5%

CI)

P

O

R (

95

% C

I)

P

Hea

vy l

oad

s 0

.95

(0

.75

-1.2

0)

0.6

7

0.5

9 (

0.3

9-0

.88

) 0

.01

1.3

8 (

0.8

2-2

.30

) 0

.22

0.9

3 (

0.7

8-1

.10

) 0

.40

0.8

9 (

0.5

8-1

.37

) 0

.59

0.9

1 (

0.5

6-1

.48

) 0

.71

Aw

kw

ard

po

sture

1

.21

(0

.81

-1.7

9)

0.3

6

1.1

3 (

0.7

6-1

.68

) 0

.53

1.0

8 (

0.7

3-1

.60

) 0

.69

1.0

1 (

0.9

1-1

.13

) 0

.82

0.8

3 (

0.5

4-1

.26

) 0

.38

0.8

1 (

0.5

1-1

.28

) 0

.36

Ob

ject

s no

t cl

ose

to

the

bo

dy

1.4

8 (

0.4

4-4

.99

) 0

.53

0.2

4 (

0.0

5-1

.17

) 0

.08

1.2

0 (

0.4

6-3

.10

) 0

.71

1.2

4 (

0.7

8-1

.98

) 0

.36

0.4

0 (

0.1

5-1

.12

) 0

.08

0.7

0 (

0.2

3-2

.17

) 0

.54

Liv

e p

eop

le/

anim

als

0.3

6 (

0.0

9-1

.47

) 0

.15

0.8

5 (

0.2

9-2

.47

) 0

.76

0.7

9 (

0.2

2-2

.80

) 0

.71

0.7

7 (

0.5

0-1

.18

) 0

.23

0.4

0 (

0.1

1-1

.50

) 0

.17

0.6

4 (

0.1

5-2

.77

) 0

.55

Unst

able

/ u

nb

alan

ce/

dif

ficult

to

gra

sp o

r ho

ld

0.8

9 (

0.5

7-1

.39

) 0

.62

0.4

2 (

0.1

4-1

.24

) 0

.12

4.0

6 (

0.8

2-

20

.06)

0.0

9

0.8

5 (

0.6

2-1

.17

) 0

.33

0.6

3 (

0.2

8-1

.42

) 0

.27

0.7

5 (

0.3

1-1

.82

) 0

.52

Vig

oro

us

ph

ysi

cal

acti

vit

y

1.0

3 (

0.7

3-1

.45

) 0

.86

0.5

6 (

0.3

0-1

.02

) 0

.06

1.9

6 (

0.9

9-3

.87

) 0

.05

0.9

2 (

0.7

4-1

.15

) 0

.48

0.9

5 (

0.5

5-1

.64

) 0

.86

1.3

7 (

0.7

3-2

.58

) 0

.33

Mo

der

ate

physi

cal

acti

vit

y

0.8

9 (

0.6

9-1

.16

) 0

.40

0.8

7 (

0.5

9-1

.29

) 0

.48

0.9

8 (

0.6

9-1

.40

) 0

.92

1.1

4 (

0.9

2-1

.41

) 0

.23

0.7

9 (

0.5

2-1

.20

) 0

.27

0.8

0 (

0.5

2-1

.24

) 0

.33

Sli

p/

trip

/ fa

ll

--

--

--

--

--

--

--

--

--

--

--

--

Co

nsu

mp

tio

n o

f al

coho

l 1

.14

(0

.37

-3.5

0)

0.8

2

1.1

6 (

0.5

4-2

.47

) 0

.71

0.8

6 (

0.3

1-2

.42

) 0

.78

0.9

0 (

0.4

2-1

.91

) 0

.78

2.1

3 (

0.4

6-9

.79

) 0

.33

1.1

5 (

0.3

5-3

.82

) 0

.81

Sex

ual

act

ivit

y

0.8

9 (

0.0

8-9

.93

) 0

.93

3.8

2 (

1.0

0-1

4.5

2)

0.0

4

1.0

0 (

0.2

9-3

.39

) 1

.00

1.1

8 (

0.8

3-1

.66

) 0

.36

1.2

1 (

0.4

4-3

.31

) 0

.71

0.6

7 (

0.2

3-1

.94

) 0

.46

Psy

ch

olo

gic

al

fact

ors

Dis

trac

ted

0

.52

(0

.14

-1.9

0)

0.3

2

0.5

0 (

0.0

6-4

.33

) 0

.53

--

--

0.8

5 (

0.1

8-4

.07

) 0

.84

--

--

0.1

6 (

0.0

1-5

.41

) 0

.31

93

Fat

igued

/ ti

red

1

.29

(0

.66

-2.5

5)

0.4

6

0.9

9 (

0.5

8-1

.71

) 0

.99

0.9

2 (

0.5

4-1

.58

) 0

.77

0.8

6 (

0.7

0-1

.06

) 0

.16

1.2

3 (

0.6

9-2

.20

) 0

.49

0.9

3 (

0.5

0-1

.73

) 0

.83

*E

nte

red

as

conti

nuo

us

var

iab

les,

incr

ease

fo

r 1

SD

. H

abit

ual

ph

ysi

cal

acti

vit

y=

35

0**;

Ag

e=1

3;

BM

I=5

; N

um

ber

of

pre

vio

us

epis

od

es=

5;

Dep

ress

ion

=3

; A

nxie

ty=

3.

** H

PA

: H

abit

ual

ph

ysi

cal

acti

vit

y i

s no

t no

rmal

dis

trib

ute

d a

nd

we

use

d I

QR

=3

50

min

s.

Bo

ld=

p<

0.0

5.

94

Ap

pen

dix

Ta

ble

4.

Exp

osu

re f

req

uen

cy a

nd

od

ds

rati

os

for

each

tri

gger

- s

eco

nd

ary a

naly

sis

(1ho

ur

win

do

w)

Tri

gg

ers

Ca

se w

ind

ow

(0-1

ho

urs

),

No

. (%

)

Fir

st c

on

tro

l w

ind

ow

(24

-25

ho

urs

),

No

. (%

)

Sec

on

d c

on

tro

l w

ind

ow

(48

-49

ho

urs

),

No

. (%

)

Od

ds

Ra

tio

(9

5%

CI)

†

P

Ph

ysi

cal

fact

ors

M

anual

task

s in

vo

lvin

g

Hea

vy l

oad

s 1

66

(1

6.6

) 5

2 (

5.2

) 5

0 (

5.0

) 6

.2 (

3.9

to 9

.7)

<0

.00

01

Aw

kw

ard

po

sture

2

59

(2

5.9

) 6

5 (

6.5

) 4

7 (

4.7

) 7

.9 (

5.4

to 1

1.8

) <

0.0

001

Obje

cts

no

t cl

ose

to

the

bo

dy

3

5 (

3.5

) 1

3 (

1.3

)

9 (

0.9

) 6

.5 (

2.3

to 1

8.6

) <

0.0

001

Liv

e p

eop

le o

r an

imal

s 7

3 (

7.3

) 5

5 (

5.5

) 5

5 (

5.5

) 5

.5 (

1.9

to 1

6.0

) 0

.00

2

Unst

able

/ u

nb

alan

ced

/ d

iffi

cult

to

gra

sp o

r ho

ld l

oad

s 4

9 (

4.9

) 1

6 (

1.6

) 1

2 (

1.2

) 7

.6 (

3.0

to 1

9.3

) <

0.0

001

M

od

erat

e o

r vig

oro

us

ph

ysi

cal

act

ivit

y

20

4 (

20

.4)

10

7 (

10

.7)

87

(8.7

) 2

.9 (

2.1

to 4

.0)

<0

.00

01

V

igo

rous

ph

ysi

cal

acti

vit

y o

nly

9

6 (

9.6

) 3

7 (

3.7

) 2

8 (

2.8

) 4

.3 (

2.6

to 7

.2)

<0

.00

01

S

lip

/ tr

ip/

fall

*

34

(3.4

) 1

(0

.1)

0 (

0.0

) --

--

S

exual

act

ivit

y

5 (

0.5

) 8

(0

.8)

9 (

0.9

) 0

.6 (

0.2

to 1

.9)

0.4

10

Psy

cho

soci

al f

acto

rs

C

onsu

mp

tio

n o

f al

coho

l 1

1 (

1.1

) 9

(0

.9)

9 (

0.9

) 1

.2 (

0.5

to 3

.0)

0.6

55

D

istr

acte

d d

uri

ng a

n a

ctiv

ity o

r ta

sk

26

(2.6

) 6

(0

.6)

8 (

0.8

) 2

1.0

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96

Triggers Specific Questions Tick the boxes where the participant reports pain on the mannequin below:

Height (cm): ______________________ Weight (Kg): _____________________

How much back pain have you had during the first 24 hours of this episode? [1]

None Very mild Mild Moderate Severe Very Severe

During the first 24 hours of this episode how much did back pain interfere with your

normal work (including both work outside the home and housework)? [1]

Not at all A little bit Moderately Quite a bit Extremely

How tense or anxious have you felt in the past week? Circle one. [2]

0 1 2 3 4 5 6 7 8 9 10

Appendix 5. Study Questionnaire

Calm and

relaxed

As

tense/anxious

as I’ve ever

felt

97

Physical Activity [3]

1. In the last week, how many times have you walked continuously, for at least 10 minutes, for

recreation, exercise or to get to or from places? ______times;


What do you estimate was the total time that you spent walking in this way in the last week?



2. In the last week, how many times did you do any vigorous physical activity which made

you breathe harder or puff and pant? (e.g. jogging, cycling, aerobics, competitive

tennis)______times;


What do you estimate was the total time that you spent doing this vigorous physical activity in

the last week? ______hours ______minutes;


3. In the last week, how many times did you do any moderate physical activities that you have

not already mentioned? (e.g. gentle swimming, social tennis, golf)______times;


What do you estimate was the total time that you spent doing these activities in the last week?


And in the week before your back pain started? ______ hours ______minutes.

4. Was your level of physical activity last week typical for you? Yes No

98

Triggers Exposure

Please write the date and time you first noticed your low back pain on the table below:

Day Fri Sat Sun Mon Tues Wed Thurs Fri Sat Sun

Date

Time

I am going to ask you to recall what you were doing in the three days leading up to

your back pain and also on the day of your back pain. To help your memory I

would like you to sit down with your diary and smartphone. To help make sure we

have the right days I want you to tell me the day, weather and a key thing you did

on each day.

Example: Tuesday: cold and wet; visited parents

Day of back pain: _______________________________________________________

Day before: ____________________________________________________________

2 days earlier: __________________________________________________________

3 days earlier: __________________________________________________________

99

1a. MANUAL TASKS …

HEAVY LOADS [4]

Day

If yes, precisely describe manual task (type of task,

load, duration and time). e.g. Lifted 50 large boxes,

one at a time, (~15kg each box – perceived as heavy)

from the floor and placed them on a bench at waist

height. 8:00am - 20min.

The first group of questions is

about manual tasks. Manual tasks

include lifting, lowering, pushing,

carrying or otherwise moving,

holding or restraining any person,

animal or item.

Firstly we are interested in manual

tasks involving HEAVY LOADS.



involving a heavy load?






OK now two days back That was


day).



day)

Day of back

pain

Yes No

Day before

Yes No

2 days earlier

Yes No

3 days earlier

Yes No

100

1b. MANUAL TASKS…

AWKWARD POSTURE [4] Day


of task, load, duration, time & body position). e.g. knelt

down while gardening. 2:00pm – 40min.


manual tasks involving an

AWKWARD POSTURE. So on the day of your back pain did


involving an awkward position?










day)

Day of back

pain

Yes No

Day before

Yes No

2 days

earlier

Yes No

3 days

earlier

Yes No

101

1c. MANUAL TASKS…

AN OBJECT THAT COULD

NOT BE POSITIONED CLOSE

TO THE BODY [4]

Day



Lifted large box (~7Kg – perceived as light) out of the

car boot and placed it on the floor. 11:00am – 10 sec.


manual tasks involving AN

OBJECT THAT COULD NOT BE

POSITIONED CLOSE TO THE

BODY.



involving an object that could not

be positioned close to the body?










day)

Day of back

pain

Yes No

Day before

Yes No

2 days

earlier

Yes No

3 days

earlier

Yes No

102

1d. MANUAL TASKS…

LIVE PEOPLE OR ANIMALS [4] Day



Lifted 2 year-old child (~12kg – perceived as moderate)

from the floor onto the bed. 8:00pm once. Lifted and

carried baby (5 kg perceived as light), 3 to 4 times from

one room to another. 8:10pm – 30min


manual tasks involving LIVE

PEOPLE OR ANIMALS.



involving live people or animals?


of the day).



of the day).



of the day).



of the day)

Day of back

pain

Yes No

Day before

Yes No

2 days

earlier

Yes No

3 days

earlier

Yes No

103

1e. MANUAL TASKS…

A LOAD THAT WAS

UNSTABLE, UNBALANCED OR

DIFFICULT TO GRASP OR

HOLD [4]

Day



lifted a 4 meter extension ladder (~12 Kg – perceived as

moderate) from the car roof racks, carried to garage

and hung on wall. 3:00pm - 5min.


manual tasks involving A LOAD

THAT WAS UNSTABLE,

UNBALANCED OR DIFFICULT

TO GRASP OR HOLD.



involving a load that was unstable,

unbalanced or difficult to grasp or

hold?












Day of back

pain

Yes No

Day before

Yes No

2 days

earlier

Yes No

3 days

earlier

Yes No

104

2a. VIGOROUS



duration. e.g. ran 10km at fast pace (5 mins per km)

10:00am - 50min.


VIGOROUS PHYSICAL




housework.

Examples of vigorous physical

activity include: running, rope

skipping, axe chopping, using heavy

tools, canoeing and truck driving.



involving VIGOROUS PHYSICAL

ACTIVITIES?



Now what about the day before…





day).



the day)

Day of back

pain

Yes No

Day before

Yes No

2 days

earlier

Yes No

3 days

earlier

Yes No

105

2b. MODERATE



duration. e.g. Mowed the lawn. 11:00am -12:00 pm.


MODERATE PHYSICAL




housework.

Examples of moderate physical

activity include: leisure cycling,

fishing, general home repairs, music

playing, golf, surfing and painting.



involving MODERATE

PHYSICAL ACTIVITIES?








day).



the day).

Day of back

pain

Yes No

Day before

Yes No

2 days

earlier

Yes No

3 days

earlier

Yes No

106

3. SLIP, TRIP OR FALL [5] Day

If yes, precisely describe incident and time. e.g.

Descending stairs, missed bottom step and jarred back.

8:30am – one occasion.

Now I want you to think about SLIP,

TRIP OR FALL.


you have a slip, trip or fall? That


the day).







OK finally three days back….



Day of back

pain

Yes No

Day before

Yes No

2 days

earlier

Yes No

3 days

earlier

Yes No

107

4. CONSUMED ALCOHOL [6] Day

If yes, specify amount (refer to standard drink table at

the end of booklet), time and duration. E.g. 2x red wine

glasses (180ml). 8:20pm – 1h.


ALCOHOL CONSUMPTION.


you consume alcohol? That was the







day).



the day)

Day of back

pain

Yes No

Day before

Yes No

2 days

earlier

Yes No

3 days

earlier

Yes No

5. SEXUAL ACTIVITY [7] Day If yes, specify time. E.g. 11:00pm


SEXUAL ACTIVITY. So on the

day of your back pain did you

engage in sexual activity? That was


day).






day).



the day)

Day of back

pain

Yes No

Day before

Yes No

2 days

earlier

Yes No

3 days

earlier

Yes No

108

6. DISTRACTION [8] Day

If yes, specify time and duration, distraction and task.

e.g. Distracted by child crying while lifting a box from

car boot and it slipped from his/her hands. 8:30am –

one occasion.

Now I want you to think about being

DISTRACTED.

So on the day of your back pain were

you DISTRACTED for any reason

while engaged in a task or activity?








day).



the day)

Day of back

pain

Yes No

Day before

Yes No

2 days

earlier

Yes No

3 days

earlier

Yes No

7. FATIGUE OR TIREDNESS [9] Day

If yes, specify time and duration. e.g. Disrupted and

poor sleep the night before as youngest child kept

waking due to earache. 3:00am – 24h.


feeling FATIGUED or TIRED. So

on the day of your back pain did you

feel FATIGUED OR TIRED? That


the day).






day).



the day)

Day of back

pain

Yes No

Day before

Yes No

2 days

earlier

Yes No

3 days

earlier

Yes No

109

8. What do you think may have triggered your low back pain? (Record what the patient thinks may have

triggered his/her episode of back pain. eg. Bent down once to pick up newspaper from lawn. 7:00am -

immediately).

___________________________________________________________________________________________

____________________________________________________________________________________________

____________________________________________________________________________________________

____________________________________________________________________________________________

____________________________________________________________________________________________

So on the day of your back pain did you

do the activity described above? That


day).

Now what about the day before…. That


day).

OK now two days back… That was the


OK finally three days back… That was

the (restate their description of the day)

Day of back pain

Yes No

Day before

Yes No

2 days earlier

Yes No

3 days earlier

Yes No

110

Reference

1. Ware J, Sherbourne C: The MOS 36-item short-form health survey (SF-36). 1.

Conceptual framework and item selection. Medical Care 1992, 30:473-483.

2. Linton S, Hellsing A, Bergstrom G: Exercise for workers with musculoskeletal

pain: does enhancing compliance decrease pain? J Occup Med 1996, 6(3):177-190.

3. Armstrong T, Bauman A, Davies J: Physical activity patterns of Australian Adults.

In. Edited by Welfare AIoHa. Canberra; 2000.

4. Australian Safety Compensation Council: National code of practice for the

prevention of musculoskeletal disorders from performing manual tasks at work.

In. Canberra; 2007.

5. Verma S, Lombardi D, Chang W, Courtney T, Huang Y, Brennan M, Mittleman M,

Ware J, Perry M: Rushing, distraction, walking on contaminated floors and risk

of slipping in limited-service restaurants: a case--crossover study. Occupational &

Environmental Medicine 2010, 68(8):575-581.

6. Vinson DC, Mabe N, Leonard LL, Alexander J, Becker J, Boyer J, Moll J: Alcohol

and injury. A case-crossover study. Arch Fam Med 1995, 4(6):505-511.

7. Dahabreh IJ, Paulus JK, Dahabreh IJ, Paulus JK: Association of episodic physical

and sexual activity with triggering of acute cardiac events: systematic review and

meta-analysis. JAMA, 305(12):1225-1233.

8. Sorock G, Lombardi D, Peng D, Hauser R, Eisen E, Herrick R, Mittleman M: Glove

use and the relative risk of acute hand injury: a case-crossover study. Journal of

Occupational & Environmental Hygiene 2004, 1(3):182-190.

9. Chen S, Fong P, Lin S, Chang C, Chan C: A case-crossover study on transient risk

factors of work-related eye injuries. Occupational & Environmental Medicine

2009, 66(8):517-522.

111

Chapter Five

Effect of weather on back pain: results from a case-crossover study

Chapter Five is published as:

Steffens D, Maher CG, Li Q, Ferreira ML, Pereira LSM, Koes BK, Latimer J. Effect of

weather on back pain: results from a case-crossover study. Arthritis Care & Research. 2014;

66:1867-1872.

112


As co-authors of the paper “Effect of weather on back pain: results from a case-crossover

study”, we confirm that Daniel Steffens has made the following contributions:


Data collection




Qiang Li Date: 01.01.2015


Leani SM Pereira Date: 01.01.2015



113

Effect of Weather on Back Pain: Results From aCase-Crossover StudyDANIEL STEFFENS,1 CHRIS G. MAHER,2 QIANG LI,2 MANUELA L. FERREIRA,2

LEANI S. M. PEREIRA,3 BART W. KOES,4 AND JANE LATIMER2

Objective. To investigate the influence of various weather conditions on risk of low back pain.Methods. We conducted a case-crossover study in primary care clinics in Sydney, Australia. A total of 993 consecutivepatients with a sudden, acute episode of back pain were recruited from October 2011 to November 2012. Following thepain onset, demographic and clinical data about the back pain episode were obtained for each participant during aninterview. Weather parameters (temperature, relative humidity, air pressure, wind speed, wind gust, wind direction, andprecipitation) were obtained from the Australian Bureau of Meteorology for the entire study period. Weather exposuresin the case window (time when participants first noticed their back pain) were compared to exposures in 2 control timewindows (same time duration, 1 week and 1 month before the case window).Results. Temperature, relative humidity, air pressure, wind direction, and precipitation showed no association withonset of back pain. Higher wind speed (odds ratio [OR] 1.17 [95% confidence interval (95% CI) 1.04–1.32], P � 0.01 foran increase of 11 km/hour) and wind gust (OR 1.14 [95% CI 1.02–1.28], P � 0.02 for an increase of 14 km/hour) increasedthe odds of pain onset.Conclusion. Weather parameters that have been linked to musculoskeletal pain such as temperature, relative humidity,air pressure, and precipitation do not increase the risk of a low back pain episode. Higher wind speed and wind gustspeed provided a small increase in risk of back pain, and although this reached statistical significance, the magnitude ofthe increase was not clinically important.

INTRODUCTION

Patients with musculoskeletal pain commonly report thatcertain weather conditions influence their symptoms, thepain from rheumatoid arthritis being a clear example ofthis (1–3). Previous studies have reported that cold orhumid weather conditions (4,5) and changes in weatherconditions (6) negatively influence symptoms in patientsexperiencing chronic pain. Despite the high frequency

with which this belief is reported, there are few robuststudies that have investigated this potential association.The key problems are that study participants are notblinded to the study hypotheses, the studies have no con-trol period, and data are mainly based on subjective recallof both weather and symptoms.

It is a methodological challenge to assess the effect of theweather on pain onset using traditional study designs. Toour knowledge, only 2 studies have assessed whether as-pects of the weather influence musculoskeletal pain usinga case-crossover methodology (3,7). The case-crossover ap-proach was specifically designed to study exposures, suchas the weather, that have a short induction time and tran-sient effect. With this design, it would be possible toevaluate the increased risk associated with aspects of theweather by comparing exposure to meteorological vari-ables at the time of the pain onset or exacerbation (definedas the case window) and in earlier periods when the per-son was pain free (defined as the control windows) (8).

Subsequent to completing a case-crossover study evalu-ating physical and psychosocial triggers for an episode oflow back pain (LBP), we became aware of the limited dataon weather and musculoskeletal pain. We took the oppor-tunity to link back pain data from the original data set andhistorical weather data obtained from meteorological re-

1Daniel Steffens, BPhty: The George Institute for GlobalHealth, Sydney Medical School, and The University of Syd-ney, Sydney, New South Wales, Australia, and Federal Uni-versity of Minas Gerais, Minas Gerais, Brazil; 2Chris G.Maher, PhD, Qiang Li, MBiostat, Manuela L. Ferreira, PhD,Jane Latimer, PhD: The George Institute for Global Health,Sydney Medical School, and The University of Sydney, Syd-ney, New South Wales, Australia; 3Leani S. M. Pereira, PhD:Federal University of Minas Gerais, Minas Gerais, Brazil;4Bart W. Koes, PhD: Erasmus MC, University Medical Cen-ter Rotterdam, Rotterdam, The Netherlands.

Address correspondence to Daniel Steffens, BPhty, TheGeorge Institute for Global Health, Sydney Medical School,The University of Sydney, PO Box M201, Missenden Road,Sydney, 2050, New South Wales, Australia. E-mail:[email protected].

Submitted for publication March 19, 2014; accepted inrevised form May 27, 2014.

Arthritis Care & ResearchVol. 66, No. 12, December 2014, pp 1867–1872DOI 10.1002/acr.22378© 2014, American College of Rheumatology

ORIGINAL ARTICLE

1867

114

cords. The aim of this study was to quantify the transientincrease in risk of sudden onset of acute LBP associatedwith the following weather parameters: temperature (°C),relative humidity (%), air pressure (hPa), wind speed (km/hour), wind gust (km/hour), wind direction (degrees true),and precipitation (mm).

SUBJECTS AND METHODS

The present study is a reanalysis of original case-crossoverstudy data (9) linked to historical weather data obtainedfrom meteorological records. Since the present study wasconceived after completion of the original case-crossoverstudy (9), the weather exposure data and back pain historydata are independent, and participants and staff wereblinded to the study hypotheses during data collection.Ethical approval for the study was granted by the Univer-sity of Sydney Human Research Ethics Committee (proto-col 05-2011/13742).

Study participants. Consecutive patients presenting toprimary care clinicians (general medical practitioners,physiotherapists, chiropractors, and pharmacists) for treat-ment of an episode of sudden-onset, acute LBP were re-cruited in Sydney, Australia, from October 2011 to No-vember 2012. To be eligible to enter the study, participantsmust have met the following criteria: 1) comprehends spo-ken English; 2) primary symptom of pain in the area be-tween the 12th rib and buttock crease, with or without legpain; 3) pain of at least moderate intensity during the first24 hours of the episode (assessed using a modified versionof item 7 of the Short Form 36 [SF-36]); 4) presentation fortreatment within 7 days from the time of pain onset; and 5)no known or suspected serious spinal pathology (e.g., met-astatic, inflammatory, or infective diseases of the spine;cauda equina syndrome; spinal fracture). A sudden-onsetepisode of LBP was defined as pain of at least moderateintensity that developed over the first 24 hours (assessedusing a modified version of item 7 of the SF-36) (10).

Participant interview. Basic demographic and clinicaldata were collected by telephone interview (9). Only thosepatients who were interviewed within 14 days from the

onset of their LBP were included. In total, 993 people withLBP participated. All participants were ages �18 years.

Meteorological data. Sydney is the state capital of NewSouth Wales and the most populous city in Australia. Ithas a temperate climate with warm summers and mildwinters, and rainfall spread throughout the year. Meteoro-logical data were obtained from the Australian Bureau ofMeteorology for the entire study period from 5 weathermonitoring stations in Sydney (www.bom.gov.au). Theweather stations were located in 3 main regions: SydneyCentral (Sydney Airport-066037), Sydney North West(Penrith Lakes-067113 and Badgerys Creek-067108), andSydney South West (Mount Annan-068257 and CamdenAirport-068192). Two weather stations (Penrith Lakes andMount Annan) did not provide data on air pressure; there-fore, air pressure data were used from 2 neighboringweather stations (Badgerys Creek and Camden Airport).For each participant enrolled in the study, we used datafrom the weather station closest to the region where theylived. The following hourly weather parameters were ob-tained: temperature (°C), relative humidity (%), air pres-sure (hPa), wind speed (sustained wind speed averagedover 10 minutes leading up to the time of the observation;km/hour), wind gust (short burst of high-speed windaveraged over 3 seconds leading up to the time of theobservation; km/hour), wind direction (direction wherethe wind is coming from; degrees true), and precipitation(mm).

Study design. To determine whether there is an associ-ation between weather parameters and LBP onset, we useda case-crossover design. This design compares exposure toweather parameters at the time of back pain onset (definedas the case window) with exposure at the same time 1week and 1 month prior to the pain onset (defined ascontrol windows 1 and 2, respectively) for each partici-pant. The time periods for exposure were defined as fol-lows: 1) within 1 hour (average value at 1 hour immedi-ately before the pain onset), 2) at 24 hours (average value at24 hours immediately before the pain onset), and 3) aver-age value within 24 hours (average value from 0–24 hoursimmediately before the pain onset).

To determine whether change in the weather parametersis associated with LBP onset, we computed a change scoreusing this formula: average value over 0–24 hours imme-diately prior to the pain onset minus average value over25–48 hours immediately prior to the pain onset for eachparticipant.

Statistical analysis. First, a descriptive analysis wasperformed. Characteristics of the study subjects and dis-tribution of weather parameters were reported. Second,the analysis followed standard methods for stratified ana-lyses. In the case-crossover design, the individual subjectis the stratifying variable (8,11). We used the matched-pairanalytical approach (conditional logistic regression) tocontrast exposures (meteorological variables) for the caseperiod with exposures for the control period. For eachsubject, 1 case period was matched to 2 control periods

Significance & Innovations● Patients with musculoskeletal pain commonly re-

port that their symptoms are influenced by theweather, but this issue has not been evaluated inrobust research or for the most common musculo-skeletal condition, back pain.

● There was no association between temperature,relative humidity, air pressure, wind direction,and precipitation and risk of back pain.

● Higher wind speeds slightly increased the odds ofback pain onset, but the effect is not important.

1868 Steffens et al

115

exactly 1 week and 1 month before the date and time of thepain onset (11). Odds ratios (ORs) and 95% confidenceintervals (95% CIs) were derived comparing exposure inthe case window with each of the 2 control windows. Allweather parameters were treated as continuous variablesand we calculated the OR associated with a 1-SD increasein the weather parameter. The analyses were performedusing Stata, version 12 (12).

RESULTS

Primary care clinicians screened 1,639 consecutive pa-tients from October 2011 to November 2012, where 993met the inclusion criteria and consented to enter the study.The characteristics of the study participants are shown inTable 1. The mean � SD age was 45.2 � 13.4 years. Mostparticipants were male (54.2%) and professional workers(34.2%), and had a mean � SD number of previous epi-sodes of back pain of 5.9 � 14.0.

During the study period of 13 months, the mean weatherparameters were 1.4 mm of precipitation (range 0.0–115.4),temperature of 16.7°C (range �0.7 to 37.5), relative humid-ity of 71.6% (range 6.0–100.0%), wind speed of 11.2 km/hour (range 0.0–74.0), wind gust of 16.2 km/hour (range0.0–100.0), wind direction of 164.6 degrees true (range360.0 to 0.0), and 1,017.3 hPa of air pressure (range 994.7–1,035.8) (Table 2).

Descriptive data for the meteorological parameters in thecase and control windows are shown in Table 3. Estimatesof fixed parameters from conditional logistic regressionmodels for each weather parameter are also shown inTable 3. Only 2 of the 28 analyses were significant: windspeed 24 hours prior to onset (OR 1.17 [95% CI 1.04–1.32],P � 0.01 for an increase of 11 km/hour) and wind gust 24hours prior to onset (OR 1.14 [95% CI 1.02–1.28], P � 0.02for an increase of 14 km/hour) increased the risk of backpain. None of the other weather parameters investigatedwas associated with back pain onset.

DISCUSSION

This study provides the first evaluation of the influence ofthe weather on the most common musculoskeletal condi-tion, back pain. Contrary to popular belief, weather param-eters, such as temperature, precipitation, air pressure,wind direction, and humidity, were not associated withthe onset of back pain. Unexpectedly, heavier wind speed24 hours prior to an episode increased the risk of backpain, but the magnitude of the effect was very small andunlikely to be clinically important. Additionally, we didnot adjust the critical P value for multiple comparisons; ifthis was done, the obtained P values of 0.01 and 0.02 forwind parameters would no longer be statistically signifi-cant.

The use of a case-crossover design is a strength of thisstudy. In case-crossover studies, cases act as their owncontrols; consequently, case-crossover studies are not con-founded by time-invariant risk factors, since exposure in-formation is collected from the same individual (11). Thetiming and nature of our study allowed us to avoid some of

the potential problems associated with the case-crossoverdesign. We avoided the problems associated with recall,since exposure data were objectively measured and ob-tained independently of the back pain data. Since bothparticipants and assessors were blinded to the study hy-potheses, we avoided bias associated with people’s beliefsabout weather and pain. Lastly, we enrolled a large andwell-defined cohort of consecutive patients from primarycare clinics.

This study has some limitations that should be takeninto account. First, our data did not include potentiallyimportant individual data, such as time spent outdoors,characteristics of housing or work, and air conditioning,which could modify a participant’s vulnerability toweather conditions. Second, we used meteorological dataobtained from 3 main regions in Sydney and assumed thatthe LBP onset occurred in the individual while in a regionclose to their home. This may have introduced misclassi-fication for some patients’ exposure. The effect of thisnondifferential bias would be to change the present find-ings toward the null (13). Using data from 3 distinctweather regions, however, helped minimize the spatialvariations in the weather parameters that exist within re-gions (14). Third, participants’ time of back pain onset wasbased on their recall, which is a potential limitation ofretrospective studies. Therefore, participants were askedto use their diary, calendar, or smartphone to help recallthe onset time. Also, to avoid time recall bias, interviewswere performed as soon as possible after the onset of backpain, with the mean � SD time between pain onset andpresentation to primary care of 3.0 � 2.1 days and frompresentation to interview of 1.9 � 1.9 days.

There is little published research investigating the effectof the weather on musculoskeletal pain. Of the 2 previouscase-crossover studies, one found no effect of relative hu-midity, pressure, rain, and hours of sun and cloud coveron symptoms of rheumatoid arthritis (3), while the otherfound that higher wind speed slightly increased the risk ofhip fracture (7), but only in a subgroup of participants.Typically, the research cited to support a relationshipbetween weather and LBP uses very weak designs. Forexample, many studies simply survey patients about theiropinion on the effect of weather on their symptoms (4–6).Sometimes the belief that weather affects musculoskeletalpain is supported by reviews of studies that report higherprevalence of musculoskeletal pain in studies conductedin cooler settings; however, there are other between-studyfactors that also could have contributed to this finding(15). At present, there is no evidence derived from robustresearch that supports the widespread belief that theweather affects musculoskeletal pain. There is, however,some evidence for other health conditions. Previous case-crossover studies have shown that exposure to lower tem-peratures increases the risk of myocardial infarction (16),whereas higher temperatures and lower pressures lead toan increase in risk of headaches (17).

Our study provides clear evidence that weather does nothave an important effect on LBP onset. Only a trivialincrease in the risk was observed with higher wind speed24 hours prior to the onset of pain in this population ofAustralian adults. One possible explanation for the lack of

Influence of Weather on Back Pain 1869

116

Table 1. Characteristics of the participants*

SydneyCentral

(n � 666)

SydneyNorth West(n � 256)

SydneySouth West

(n � 71)Overall

(n � 993)

Male sex 356 (53.5) 138 (53.9) 44 (61.9) 538 (54.2)Age, mean � SD years 45.0 � 14.2 45.3 � 11.8 47.2 � 11.6 45.2 � 13.4Height, mean � SD cm 172.9 � 10.3 170.6 � 9.9 173.9 � 12.2 172.4 � 10.4Weight, mean � SD kg 78.8 � 17.7† 78.7 � 19.4 80.2 � 17.7 78.8 � 18.1‡BMI, mean � SD kg/m2 26.2 � 5.0† 26.9 � 5.9 26.4 � 4.4 26.4 � 5.2‡Duration of current episode, mean � SD days 5.1 � 2.7 4.5 � 2.8 4.9 � 2.9 4.9 � 2.7No. of previous episodes, mean � SD 6.3 � 15.9 4.7 � 7.7 6.2 � 12.6 5.9 � 14.0Days to seek care, mean � SD 3.0 � 2.1 2.7 � 2.1 2.9 � 2.0 3.0 � 2.1Days of reduced activity, mean � SD 2.4 � 2.2 1.9 � 1.9 3.0 � 2.3 2.3 � 2.2Depression status, mean � SD 2.7 � 2.6 2.7 � 2.8 2.9 � 2.8 2.7 � 2.7Pain, mean � SD 5.1 � 2.1 5.7 � 2.1 5.4 � 2.1 5.3 � 2.1GPES, mean � SD 1.8 � 1.8 1.7 � 1.7 1.7 � 1.9 1.8 � 1.8Tense/anxious, mean � SD 4.0 � 2.5 4.1 � 2.7 4.1 � 2.6 4.0 � 2.5Presence of leg pain 64 (9.6) 27 (10.5) 10 (14.1) 101 (10.2)Compensation 47 (7.1) 26 (10.2) 15 (21.1) 88 (8.9)Medication 320 (48.1) 98 (38.3) 32 (45.1) 450 (45.3)What do you do for a living?

Not employed 124 (18.6) 29 (11.3) 9 (12.7) 162 (16.3)Clerical and administrative worker 69 (10.4) 30 (11.7) 4 (5.6) 103 (10.4)Community and personal service worker 31 (4.7) 15 (5.9) 1 (1.4) 47 (4.7)Laborer 13 (2.0) 10 (3.9) 7 (9.9) 30 (3.0)Machinery operator and driver 14 (2.1) 10 (3.9) 3 (4.2) 27 (2.7)Manager 106 (15.9) 39 (15.2) 11 (15.5) 156 (15.7)Professional 234 (35.1) 83 (32.4) 23 (32.4) 340 (34.2)Sales worker 33 (5.0) 17 (6.6) 2 (2.8) 52 (5.2)Technician and trade worker 42 (6.3) 23 (9.0) 11 (15.5) 76 (7.7)

Pain location§Upper back 39 (5.9) 18 (7.0) 2 (2.8) 59 (5.9)Lower back 666 (100.0) 256 (100.0) 71 (100.0) 993 (100.0)Left thigh (back) 65 (9.8) 19 (7.4) 11 (75.5) 95 (9.6)Left leg (back) 22 (3.3) 15 (5.9) 5 (7.0) 42 (4.2)Right thigh (back) 72 (10.8) 23 (9.0) 12 (16.9) 107 (10.8)Right leg (back) 31 (4.7) 12 (4.7) 5 (7.0) 48 (4.8)Right thigh (front) 20 (3.0) 8 (3.1) 1 (1.4) 29 (2.9)Right leg (front) 8 (1.2) 3 (1.2) 0 (0.0) 11 (1.1)Left thigh (front) 20 (3.0) 3 (1.2) 3 (4.2) 26 (2.6)Left leg (front) 5 (0.8) 2 (0.8) 0 (0.0) 7 (0.7)

Pain severityModerate 251 (37.7) 98 (38.3) 22 (31.0) 371 (37.4)Severe 328 (49.3) 127 (49.6) 36 (50.7) 491 (49.5)Very severe 87 (13.1) 31 (12.1) 13 (18.3) 131 (13.2)

Pain interfering workNot at all 16 (2.4) 5 (2.0) 0 (0.0) 21 (2.1)A little bit 75 (11.3) 24 (9.4) 2 (2.8) 101 (10.2)Moderately 161 (24.2) 72 (28.1) 15 (21.1) 248 (25.0)Quite a bit 259 (38.9) 97 (37.9) 30 (42.3) 386 (38.9)Extremely 155 (23.3) 58 (22.7) 24 (33.8) 237 (23.9)

Habitual physical activity in the last week¶Sedentary 346 (51.9) 149 (58.2) 43 (60.5) 538 (54.2)Insufficient activity 114 (17.1) 34 (13.2) 15 (21.1) 163 (16.4)Sufficient activity 206 (30.9) 73 (28.5) 13 (18.3) 292 (29.4)

Habitual physical activity in the week before¶Sedentary 212 (31.8) 112 (43.7) 33 (46.5) 357 (35.9)Insufficient activity 122 (18.3) 41 (16.0) 11 (15.5) 174 (17.5)Sufficient activity 332 (49.8) 103 (40.2) 27 (38.0) 462 (45.5)

* Values are the number (percentage) unless indicated otherwise. BMI � body mass index; GPES � Global Perceived Effect Score.† N � 665.‡ N � 992.§ Pain location was assessed using a pain manikin provided to participants by the referring clinician.¶ Habitual physical activity � moderate activity time � (2 � vigorous activity time). Sedentary � 0 minutes, insufficient activity � �1 to �149minutes, and sufficient activity � �150 minutes.

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effect in our results may be the temperate climate of theSydney region where the study was conducted. Regions

with more extreme weather conditions may present a dif-ferent result, but further research is needed. Interestingly,

Table 2. Features of weather parameters in 3 Sydney conurbations from October 2011 to November 2012

Sydney Central Sydney South West Sydney North West

Mean � SD* Min Max Mean � SD* Min Max Mean � SD* Min Max

Precipitation, mm 1.4 � 4.9 0.0 75.4 1.5 � 5.9 0.0 115.4 1.3 � 5.0 0.0 80.0Temperature, °C 17.9 � 4.6 6.0 37.5 16.8 � 6.0 1.1 37.1 15.5 � 6.1 �0.7 37.4Relative humidity, % 65.8 � 18.0 6.0 100.0 75.2 � 23.1 11.0 100.0 73.8 � 21.0 10.0 99.0Wind speed, km/hour 19.9 � 9.9 0.0 74.0 6.9 � 5.9 0.0 50.0 7.0 � 5.3 0.0 33.0Wind gust, km/hour 25.6 � 12.9 0.0 100.0 11.0 � 9.2 0.0 74.0 12.0 � 9.0 0.0 61.0Wind direction, degrees true 190.9 � 106.0 0.0 360.0 163.1 � 111.3 0.0 360.0 139.6 � 108.1 0.0 360.0Air pressure, hPa 1,017.2 � 6.4 994.7 1,035.3 1,017.3 � 6.5 995.6 1,035.7 1,017.3 � 6.6 995.0 1,035.8

* Values are the mean � SD of hourly measures for the study period.

Table 3. Exposure and estimates of fixed parameters for included weather conditions (n � 993)*

Case window(onset day)

Control window1 (1 week ago)

Control window2 (1 month ago) OR (95% CI)† P 1 SD†

Precipitation, mmWithin 1 hour‡ 1.12 � 4.36 1.24 � 5.45 1.21 � 4.75 0.98 (0.89–1.07) 0.59 5At 24 hours§ 1.14 � 5.02 1.20 � 4.56 1.25 � 4.89 0.98 (0.89–1.09) 0.76 5Average value over 24 hours¶ 1.20 � 3.42 1.36 � 4.15 1.35 � 3.77 0.95 (0.87–1.05) 0.32 4Change from 0–24 to 25–48 hours# 0.15 � 4.05 �0.23 � 4.58 0.03 � 4.90 1.08 (1.00–1.18) 0.05 4

Temperature, °CWithin 1 hour‡ 17.72 � 5.36 17.64 � 5.44 17.26 � 5.72 1.05 (0.90–1.22) 0.52 5At 24 hours§ 17.65 � 5.46 17.61 � 5.52 17.21 � 5.56 1.03 (0.88–1.19) 0.75 5Average value over 24 hours¶ 16.91 � 4.28 16.95 � 4.33 16.55 � 4.60 0.96 (0.82–1.13) 0.63 4Change from 0–24 to 25–48 hours# �0.03 � 2.32 �0.13 � 2.17 �0.17 � 2.12 1.04 (0.96–1.13) 0.30 2

Relative humidity, %Within 1 hour‡ 62.92 � 20.74 63.94 � 20.36 64.84 � 20.53 0.91 (0.81–1.03) 0.14 21At 24 hours§ 63.29 � 21.05 64.16 � 20.99 64.32 � 20.72 0.93 (0.82–1.04) 0.20 21Average value over 24 hours¶ 66.36 � 14.37 67.27 � 13.90 67.78 � 13.96 0.92 (0.83–1.01) 0.09 14Change from 0–24 to 25–48 hours# 0.67 � 12.19 0.72 � 11.88 0.38 � 11.55 1.00 (0.91–1.09) 0.93 12

Wind speed, km/hourWithin 1 hour‡ 16.56 � 10.37 16.55 � 10.78 16.32 � 10.67 1.00 (0.89–1.13) 0.99 11At 24 hours§ 17.26 � 10.90 16.30 � 10.60 16.45 � 11.04 1.17 (1.04–1.32) 0.01 11Average value over 24 hours¶ 16.11 � 8.38 15.77 � 8.44 15.74 � 8.82 1.09 (0.96–1.23) 0.19 8Change from 0–24 to 25–48 hours# �0.15 � 6.14 �0.10 � 5.89 �0.68 � 6.19 0.99 (0.91–1.08) 0.85 6

Wind gust, km/hourWithin 1 hour‡ 22.41 � 13.16 22.53 � 13.92 22.05 � 13.53 0.99 (0.88–1.11) 0.81 14At 24 hours§ 23.22 � 13.88 22.08 � 13.43 22.38 � 14.20 1.14 (1.02–1.28) 0.02 14Average value over 24 hours¶ 21.54 � 10.24 21.16 � 10.39 21.14 � 11.00 1.07 (0.95–1.20) 0.26 10Change from 0–24 to 25–48 hours# �0.16 � 8.43 �0.16 � 8.08 �0.96 � 8.49 1.00 (0.92–1.09) 1.00 8

Wind direction, degrees trueWithin 1 hour‡ 186.01 � 107.96 182.36 � 107.00 194.28 � 104.60 1.05 (0.95–1.16) 0.39 107At 24 hours§ 191.75 � 102.40 194.45 � 106.80 189.42 � 108.09 0.97 (0.87–1.07) 0.51 107Average value over 24 hours¶ 186.67 � 59.92 184.78 � 59.87 187.39 � 59.66 1.05 (0.94–1.18) 0.36 60Change from 0–24 to 25–48 hours# �0.06 � 53.94 0.25 � 54.38 0.79 � 55.69 0.99 (0.91–1.08) 0.90 54

Air pressure, hPaWithin 1 hour‡ 1,017.65 � 6.49 1,017.26 � 6.53 1,017.34 � 6.40 1.06 (0.98–1.16) 0.16 6At 24 hours§ 1,017.62 � 6.39 1,017.23 � 6.31 1,017.29 � 6.49 1.07 (0.98–1.17) 0.14 6Average value over 24 hours¶ 1,017.61 � 6.03 1,017.12 � 6.08 1,017.23 � 6.04 1.09 (1.00–1.19) 0.06 6Change from 0–24 to 25–48 hours# �0.13 � 4.85 0.09 � 4.91 0.08 � 4.63 0.95 (0.86–1.04) 0.28 5

* Values are the mean � SD unless indicated otherwise. OR � odds ratio; 95% CI � 95% confidence interval.† Per 1-SD increase.‡ Exposure defined as the value at 1 hour immediately before the pain onset.§ Exposure defined as the value at 24 hours immediately before the pain onset.¶ Exposure defined as the average value from 0–24 hours immediately before the pain onset.# Exposure defined as the average value from 0–24 hours immediately before the pain onset minus the average value from 25–48 hours the day beforepain onset.

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the popular belief about temperature, precipitation, airpressure, wind direction, and humidity and their associa-tion with back pain seems to be stronger than the datawould support. It should be noted, however, that theremay be musculoskeletal conditions other than LBP thatmay be affected by weather parameters, and this is animportant area for further research.

Further studies are needed to confirm our findings inwider populations and also to determine whether there isa subgroup of people in whom weather is more stronglyassociated with back pain onset. Case-crossover designscould be conducted in other musculoskeletal pain condi-tions. The importance of indoor temperatures, character-istics of housing or work, and air conditioning use shouldbe taken into account, since if a majority of the eventsoccur within the home, the results obtained in relation tometeorological variables may be biased toward the nullvalue. The small association found with higher windspeed may be better explained in regions where summerand winter are generally relatively extreme, rather than themoderate hot and cold of temperate regions.

In addition, co-exposure to multiple triggers (e.g., phys-ical and meteorological factors) may increase risk of backpain more than simple exposure to one meteorologicaltrigger. We are unaware of any study that has investigatedthis for musculoskeletal conditions. Additionally, usingthe case-crossover design to investigate whether exposureto weather parameters is associated with pain exacerbationor flares, in a sample of people with chronic back pain,may provide useful explanations for disease etiology andhow to improve quality of life.

In conclusion, this study shows that common weatherparameters previously believed to influence musculoskel-etal pain do not increase the risk of an episode of LBP. Thisstudy did, however, find a weak association between ex-posure to higher wind speed, wind gust, and back painonset, but the magnitude of this effect was small andtherefore not clinically important.

ACKNOWLEDGMENTSThe authors would like to thank all of the clinicians whoparticipated in the TRIGGERS for low back pain study.

AUTHOR CONTRIBUTIONS

All authors were involved in drafting the article or revising itcritically for important intellectual content, and all authors ap-proved the final version to be published. Mr. Steffens had fullaccess to all of the data in the study and takes responsibility forthe integrity of the data and the accuracy of the data analysis.Study conception and design. Steffens, Maher, Li, Ferreira,Pereira, Koes, Latimer.Acquisition of data. Steffens, Maher, Li, Ferreira, Pereira, Koes,Latimer.

Analysis and interpretation of data. Steffens, Maher, Li, Ferreira,Pereira, Koes, Latimer.

REFERENCES

1. Patberg WR, Rasker JJ. Weather effects in rheumatoid arthritis:from controversy to consensus. A review. J Rheumatol 2004;31:1327–34.

2. Smedslund G, Mowinckel P, Heiberg T, Kvien TK, Hagen KB.Does the weather really matter? A cohort study of influencesof weather and solar conditions on daily variations of jointpain in patients with rheumatoid arthritis. Arthritis Rheum2009;61:1243–7.

3. Abasolo L, Tobias A, Leon L, Carmona L, Fernandez-Rueda JL,Rodriguez AB, et al. Weather conditions may worsen symp-toms in rheumatoid arthritis patients: the possible effect oftemperature. Reumatol Clin 2013;9:226–8.

4. Shutty MS Jr, Cundiff G, DeGood DE. Pain complaint and theweather: weather sensitivity and symptom complaints inchronic pain patients. Pain 1992;49:199–204.

5. Jamison RN, Anderson KO, Slater MA. Weather changes andpain: perceived influence of local climate on pain complaintin chronic pain patients. Pain 1995;61:309–15.

6. Roth-Isigkeit A, Thyen U, Stoven H, Schwarzenberger J,Schmucker P. Pain among children and adolescents: restric-tions in daily living and triggering factors. Pediatrics 2005;115:e152–62.

7. Tenias JM, Estarlich M, Fuentes-Leonarte V, Iniguez C, Ball-ester F. Short-term relationship between meteorological vari-ables and hip fractures: an analysis carried out in a health areaof the Autonomous Region of Valencia, Spain (1996-2005).Bone 2009;45:794–8.

8. Maclure M. The case-crossover design: a method for studyingtransient effects on the risk of acute events. Am J Epidemiol1991;133:144–53.

9. Steffens D, Ferreira ML, Maher CG, Latimer J, Koes BW, BlythFM, et al. Triggers for an episode of sudden onset low backpain: study protocol. BMC Musculoskelet Disord 2012;13:7.

10. De Vet HC, Heymans MW, Dunn KM, Pope DP, van der BeekAJ, Macfarlane GJ, et al. Episodes of low back pain: a proposalfor uniform definitions to be used in research. Spine 2002;27:2409–16.

11. Mittleman MA, Maclure M, Robins JM. Control samplingstrategies for case-crossover studies: an assessment of relativeefficiency. Am J Epidemiol 1995;142:91–8.

12. StataCorp. Stata statistical software. College Station (TX):StataCorp; 2013.

13. Tsuchihashi Y, Yorifuji T, Takao S, Suzuki E, Mori S, Doi H,et al. Environmental factors and seasonal influenza onset inOkayama city, Japan: case-crossover study. Acta MedOkayama 2011;65:97–103.

14. Vaneckova P, Bambrick H. Cause-specific hospital admissionson hot days in Sydney, Australia. PloS One 2013;8:e55459.

15. Pienimaki T. Cold exposure and musculoskeletal disordersand diseases: a review. Int J Circumpolar Health 2002;61:173–82.

16. Madrigano J, Mittleman MA, Baccarelli A, Goldberg R, MellyS, von Klot S, et al. Temperature, myocardial infarction, andmortality: effect modification by individual- and area-levelcharacteristics. Epidemiology 2013;24:439–46.

17. Mukamal KJ, Wellenius GA, Suh HH, Mittleman MA.Weather and air pollution as triggers of severe headaches.Neurology 2009;72:922–7.

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Chapter Six

Does magnetic resonance imaging predict future low back pain? A systematic review

Chapter Six is published as:


resonance imaging predict future low back pain? A systematic review. European Journal of

Pain. 2014; 18:755-765.

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As co-authors of the paper “Does magnetic resonance imaging predict future low back pain?

A systematic review”, we confirm that Daniel Steffens has made the following contributions:

Data extraction, analysis and interpretation of the findings




Ciaran Williams Date: 01.01.2015

Tue S Jensen Date: 01.01.2015


121

REVIEW ARTICLE

Does magnetic resonance imaging predict future low backpain? A systematic reviewD. Steffens1, M.J. Hancock2, C.G. Maher1, C. Williams3, T.S. Jensen4,5, J. Latimer1

1 The George Institute for Global Health, Sydney Medical School, The University of Sydney, Australia

2 Discipline of Physiotherapy, Faculty of Human Sciences, Macquarie University, Sydney, Australia

3 Active Physiotherapy Newtown, Sydney, Australia

4 Research Department, The Spine Centre of Southern Denmark, Middelfart, Denmark

5 Institute of Regional Health Services Research, Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark

CorrespondenceDaniel Steffens

E-mail: [email protected]

Funding sourcesNone.

Conflict of interestNone declared.

Accepted for publication22 October 2013

doi:10.1002/j.1532-2149.2013.00427.x

Abstract

Background and Objective: Magnetic resonance imaging (MRI) has thepotential to identify pathology responsible for low back pain (LBP).However, the importance of findings on MRI remains controversial. Weaimed to systematically review whether MRI findings of the lumbar spinepredict future LBP in different samples with and without LBP.Databases and Data Treatment: MEDLINE, CINAHL and EMBASEdatabases were searched. Included were prospective cohort studies investi-gating the relationship between baseline MRI abnormalities of the lumbarspine and clinically important LBP outcome at follow-up. We excludedcohorts with specific diseases as the cause of their LBP. Associationsbetween MRI findings and LBP pain outcomes were extracted from eligiblestudies.Results: A total of 12 studies met the inclusion criteria. Six studiespresented data on participants with current LBP; one included a samplewith no current LBP, three included a sample with no history of LBP andtwo included mixed samples. Due to small sample size, poor overallquality and the heterogeneity between studies in terms of participants,MRI findings and clinical outcomes investigated, it was not possible topool findings. No consistent associations between MRI findings and out-comes were identified. Single studies reported significant associations forModic changes type 1 with pain, disc degeneration with disability insamples with current LBP and disc herniation with pain in a mixedsample.Conclusions: The limited number, heterogeneity and overall qualityof the studies do not permit definite conclusions on the association ofMRI findings of the lumbar spine with future LBP (PROSPERO:CRD42012002342).

1. Introduction

Despite the enormous costs of low back pain (LBP)and thousands of clinical trials, little progress has beenmade in the management of LBP with most treat-ments having only small effects (Deyo, 2004; Kelleret al., 2007). Limited understanding of the aetiology of

LBP is likely to be a major contributor to the lack ofprogress in management. After excluding people withnerve root pain and serious pathologies (e.g., fractureand cancer), around 90–95% of LBP sufferers are clas-sified as having non-specific low back pain (NSLBP)reflecting the inability to identify a clear source for thepain (van Tulder et al., 2006). If the source of pain

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could be identified in at least some of these patientsthen it is possible that more targeted and effectivetreatments could be found.

Magnetic resonance imaging (MRI) has the poten-tial to identify pathology responsible for LBP(Schwarzer et al., 1995); however, the importance offindings on MRI remains controversial (Modic andRoss, 2007). Previous studies reveal high rates ofabnormalities on MRI in people without LBP (Bodenet al., 1990; Boos et al., 1995, 2000; Jarvik et al.,2001). Consequently, it can be difficult to determinewhether abnormalities seen on MRI are truly thecause of LBP since morphological changes arecommon in asymptomatic subjects. The lack of awidely accepted gold standard test contributes to thedifficulty in assessing the diagnostic accuracy of MRIfindings (Hancock et al., 2012).

The presence of pathology on MRI in peoplewithout LBP does not necessarily mean MRI findingsare not important to the aetiology of LBP (Hancocket al., 2012). In many other health conditions (e.g.,cardiovascular disease), pathology (e.g., atherosclero-sis) exists in people without current symptoms;however, this pathology has been shown to be veryimportant to the aetiology of the disorder (Duncanet al., 2007). MRI findings in currently asymptomaticpeople may represent markers of early pre-symptomatic disease that is later characterized by epi-sodes of pain and/or disability.

Most previous research investigating the associationbetween MRI and LBP has been cross sectional. Thesestudies provide only weak evidence of the importance

or otherwise of MRI findings to the development orcourse of LBP (Endean et al., 2011). Longitudinalstudies provide the possibility to investigate if MRIfindings are associated with important outcomes suchas the development of future LBP in currently asymp-tomatic people or the course of LBP in people withcurrent LBP. We are unaware of any previous system-atic review of prospective longitudinal studies investi-gating the association between MRI findings of thelumbar spine and future LBP. Therefore, the specificreview questions were:(1) Do MRI findings predict future LBP in people withno history of LBP?(2) Do MRI findings predict future LBP in people withno current LBP, but a previous history of LBP?(3) Do MRI findings predict the course of LBP inpeople with current LBP?(4) Do MRI findings predict future LBP in a mixedsample of participants with and without current LBP?

2. Methods

A review protocol was specified in advance and registeredon PROSPERO: International prospective register of sys-tematic reviews (http://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD42012002342).

2.1 Search strategy

A systematic search of the literature from the earliest recordto the first week of May 2012 was undertaken using a highlysensitive search strategy suggested by the Cochrane BackReview Group together with a strategy for searchingMEDLINE for prognosis studies. We combined text and,where appropriate, Medical Subject Headings terms for LBP,back pain or backache; and inception, survival, life tables, logrank, prospective or follow-up studies; and magnetic reso-nance imaging. The complete search strategies from all data-bases are included in Supporting Information Appendix S1.We identified relevant studies by electronic searches ofgeneral biomedical and science databases (MEDLINE,CINAHL and EMBASE), as well as examined the referencelists of identified papers. A final list of included studies wassent to experts in the field who reviewed the list for possibleomissions. This search had no language restrictions.

2.2 Study selection

To be included, studies were required to meet all of thefollowing criteria:(a) Prospective cohort study. This included secondary analy-sis of randomized controlled trials (RCTs), but only wherethe treatment provided was conservative, or data on theconservative arm were presented separately to the surgicalarm.

Databases• We identified relevant studies by conducting

electronic searches of MEDLINE, CINAHL andEMBASE, and by examining the reference lists ofidentified papers.

What does this study add?• No consistent associations were identified across

multiple studies.• Only Modic changes and disc degeneration at

baseline predicted poor outcome from low backpain at follow-up in single studies.

• The importance of magnetic resonance imaging(MRI) findings in predicting clinical outcomes isunclear due to the limited number and quality ofstudies and the heterogeneity between studies interms of the participants, MRI findings and clini-cal outcomes investigated.

MRI predicting future LBP D. Steffens et al.

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(b) Participants underwent baseline MRI reporting anyabnormality of the lumbar spine (e.g., but not limited to discdegeneration, disc herniation, facet joint arthropathy, Modicchanges, high intensity zone).(c) Reported a clinically important LBP outcome atfollow-up (e.g., pain, disability or a global measure ofrecovery).(d) The association between MRI findings (baseline orchange) and LBP outcomes (or sufficient raw data to calcu-late a measure of association) was reported. Simply reportinga p-value was insufficient to meet this criterion.

We excluded studies that included patients with specificdiseases such as tumours, fractures, inflammatory arthritisand cauda equina syndrome, but not sciatica. One reviewerscreened the titles and abstracts to exclude clearly irrelevantarticles. For each potentially eligible study, the full articlewas obtained and independently assessed for inclusion bytwo review authors (D.S., M.J.H., C.G.M., J.L., C.W. orT.S.J.). Any discrepancies were resolved by discussion.

2.3 Data extraction

2.3.1 Study characteristics

Data extraction was completed independently by tworeviewers. Included studies were categorized into four maingroups: (1) sample with current LBP; (2) mixed sample ofpeople with and without current LBP; (3) sample with nocurrent LBP, but previous LBP; and (4) sample with nohistory of LBP. Data were extracted from the selected studiesregarding number of subjects, sample source, age, follow-upduration, MRI findings, clinical outcomes and strength ofassociation between MRI finding and clinical outcome.When sufficient raw data were available, odds ratios (OR)and 95% confidence intervals (95% CI) were calculated.

2.3.2 Methodological quality

The methodological quality of each of the studies wasassessed independently by two reviewers (D.S., M.J.H.,C.G.M., J.L., C.W. or T.S.J.) using a standardized checklist ofpre-defined criteria (Pengel et al., 2003; Costa et al., 2012).The checklist is a modified version based on theoretical con-siderations and methodological aspects described by Altman(2001). These criteria comprised (1) definition of studysample (description of participant source and inclusion andexclusion criteria); (2) representative sample of the targetsample (participants selected by random selection or as con-secutive cases); (3) follow-up rate >80% (outcome data wereavailable for at least 80% of participants at 3-monthfollow-up or later); (4) adequate follow-up time (at least oneprognostic outcome was followed up at 3 months or later);(5) interpretable prognostic outcomes available (raw data,percentages, survival rates or continuous outcome reported);and (6) blinding (assessor unaware of at least one prognosticfactor, used to predict prognostic outcome, at the time prog-nostic outcome was measured). Disagreements among the

reviewers were discussed and resolved during a consensusmeeting. Each criteria was scored positive ‘Yes’ or negative‘No’. A positive score indicates sufficient information and apositive assessment. The same criteria have been used inprevious systematic reviews on the prognosis of acute LBP(Pengel et al., 2003; Costa et al., 2012). Methodologicalquality was not an inclusion criterion.

2.4 Analysis

Our intention was to pool results, but due to the heterogene-ity between the studies in terms of the participants, MRIfindings and clinical outcomes, it was not possible or appro-priate to pool findings. The results are presented descriptively.

Studies of participants with current LBP were used toinvestigate if MRI findings predicted the course of LBP.Studies of participants with no current LBP were used toassess if MRI findings were risk factors for future LBP.

3. Results

3.1 Selection of studies

Our search identified 6666 citations (2304 MEDLINE,265 CINAHL, 4635 EMBASE) after removing all dupli-cates (n = 538). After review of title and abstract, 6608records were excluded. Five additional studies thatmet the inclusion criteria were identified after consul-tation with experts in the field, resulting in a total of63 full-text articles eligible for assessment. Whenreviewing full-text articles for the 63 articles, a further23 were excluded as they were not prospectivestudies, 16 did not assess a LBP outcome at follow-up,8 did not present an association between MRI findingsand LBP outcome (or provide raw data to enable cal-culation of this) and 4 did not perform MRI at base-line. A table of excluded full-text articles and theprimary reason for exclusion is included in SupportingInformation Appendix S2. Therefore, 13 studies metall the inclusion criteria (Borenstein et al., 2001;Elfering et al., 2002; Carragee et al., 2005, 2006a,b;Jarvik et al., 2005; Modic et al., 2005; Kleinstucket al., 2006; McNee et al., 2011; Hellum et al., 2012;Jensen et al., 2012; Keller et al., 2012) (Fig. 1). Forone study, results from the same cohort were identi-fied in two different publications (Carragee et al.,2006a,b), but only the published report with the fullresults was included in our analysis (Carragee et al.,2006a). Consequently, the methodological quality andresults are based on 12 studies.

3.2 Methodological quality

Most studies defined the study sample (91.5%). Onlyfour studies (33%) described methods for assembling a

D. Steffens et al. MRI predicting future LBP


124

representative sample of the target sample. Ninestudies (75%) had a follow-up of at least 80% and allstudies had a follow-up for at least one prognosticoutcome at 3 months or longer and quantified progno-sis. Eleven studies used blinded assessment (91.5%).Data for individual studies are presented in Table 1.

3.3 Study characteristics

A comprehensive description of each study is providedin Table 2. Six studies included a sample of currentLBP (Modic et al., 2005; Kleinstuck et al., 2006;McNee et al., 2011; Hellum et al., 2012; Jensen et al.,

2012; Keller et al., 2012); two included a mixedsample of people with and without LBP (Carrageeet al., 2005, 2006a), one included a sample with nocurrent LBP, but previous LBP symptoms (Jarvik et al.,2005), and three studies included a sample of patientswith no history of LBP (Boos et al., 2000; Borensteinet al., 2001; Elfering et al., 2002).

The samples were recruited from primary healthcare (Elfering et al., 2002; Jarvik et al., 2005;Kleinstuck et al., 2006), secondary health care (Booset al., 2000; Carragee et al., 2005, 2006a; Modic et al.,2005; McNee et al., 2011; Hellum et al., 2012; Jensenet al., 2012; Keller et al., 2012) or volunteers from thecommunity (Borenstein et al., 2001). The majority ofthe studies focused largely or completely on men andwomen of working age, but some also included olderparticipants (ranging from 18 to 84 years old). Thefollow-up period ranged from 12 to 84 months.

3.4 Association of MRI findings withclinical outcomes

Due to the heterogeneity of samples, MRI findings andclinical outcomes, it was not possible to combine theresults of the studies included. The findings of all 12included studies are presented in Tables 3 and Figs. 2and 3.

ORs and 95% CI were calculated from the extractedraw data for the following studies (Boos et al., 2000;Elfering et al., 2002; Carragee et al., 2006a; McNeeet al., 2011; Hellum et al., 2012; Jensen et al., 2012).

Records identified through searches

MEDLINE = 2304CINAHL = 265EMBASE = 4635

(n = 7204)

Records screened after duplicates removed

(n = 6666)

Full-text articles assessed for eligibility

(n = 63)

Studies included -12 different cohorts

(n = 13)

Duplicate records excluded(n = 538)

Records excluded• Not related to low back pain;• Ineligible designs;• No MRI at baseline.

(n = 6608)

Records excluded• 23 not a prospective study;• 8 no association between

MRI findings and LBP outcome;

• 16 no LBP outcome at follow-up;

• 4 no MRI at baseline.(n = 51)

Full-text articles identified by

experts in the field (n = 5)

Figure 1 Flowchart of search strategy.

Table 1 Methodological quality assessment of included studies.

Study

Definition of

study samplea

Representative

sampleb

Follow-up rate

>80%c

Follow-up >3

monthsd

Outcomes

reportede

Blinded

outcomef

Borenstein et al., 2001 Yes No No Yes Yes Yes

Carragee et al., 2006a Yes Yes Yes Yes Yes Yes

Carragee et al., 2005 Yes Yes Yes Yes Yes Yes

Elfering et al., 2002 No No Yes Yes Yes No

Jarvik et al., 2005 Yes Yes Yes Yes Yes No

Keller et al., 2012 Yes No No Yes Yes Yes

McNee et al., 2011 Yes Yes No Yes Yes Yes

Jensen et al., 2012 Yes No Yes Yes Yes Yes

Kleinstuck et al., 2006 Yes No Yes Yes Yes Yes

Modic et al., 2005 Yes No Yes Yes Yes Yes

Boos et al., 2000 Yes No Yes Yes Yes Yes

Hellum et al., 2012 Yes No Yes Yes Yes Yes

aDescription of participant source and inclusion and exclusion criteria.bParticipants selected by random selection or as consecutive cases.cOutcome data were available for at least 80% of participants at 3-month follow-up or later.dAt least one prognostic outcome was followed up at 3 months or later.eRaw data, percentages, survival rates or continuous outcome reported.fAssessor unaware of at least one prognostic factor, used to predict prognostic outcome, at time prognostic outcome was measured.



125

Tab

le2

Ind

ivid

uals

tud

ych

arac

teri

stic

s.

Stud

ySa

mp

leso

urce

Mea

nag

e

(ran

ge)

MR

Ifind

ings

MR

Isco

ring

(thr

esho

ld)

Clin

ical

outc

omes

Out

com

esc

orin

g

(thr

esho

ld)

Follo

w-u

p,

dur

atio

n(%

)

Pop

ulat

ion

with

curr

ent

LBP

Kelle

ret

al.,

2012

269

pat

ient

sre

ferr

edto

univ

ersi

ty

spin

ecl

inic

49.7

(20–

60)

Mod

icch

ange

sty

pe

1Ye

s/N

o(p

rese

nt)

Patie

ntgl

obal

imp

ress

ion

of

imp

rove

men

t(P

GI-I

)

1–7

(≥3

not

reco

vere

d)

12m

onth

s(4

0%)

Mod

icch

ange

sty

pe

2Ye

s/N

o(p

rese

nt)

Patie

ntgl

obal

imp

ress

ion

of

imp

rove

men

t(P

GI-I

)

1–7

(≥3

not

reco

vere

d)

Hel

lum

etal

.,

2012

66tr

ialp

artic

ipan

tsre

crui

ted

from

univ

ersi

tyho

spita

ls(o

nly

par

ticip

ants

inco

nser

vativ

e

grou

p)

41.5

(?)

Mod

icch

ange

sty

pe

1Ye

s/N

o(p

rese

nt)

Dis

abili

ty(O

DI)

0–10

0(≥

15p

oint

s)12

mon

ths

(100

%)

Mod

icch

ange

sty

pe

2Ye

s/N

o(p

rese

nt)

Dis

cd

egen

erat

ion

(hei

ght

red

uctio

n)

%re

duc

tion

(≥40

%)

Dis

cd

egen

erat

ion

(sig

nali

nten

sity

)G

rad

ed1

to4

(>3)

Face

tjo

int

arth

opat

hyN

oor

slig

htto

≥mod

erat

e(≥

mod

erat

e)

Hig

h-in

tens

ityzo

neYe

s/N

o(p

rese

nt)

McN

eeet

al.,

2011

323

pat

ient

sof

hosp

italr

adio

logy

dep

artm

ent

?(20

–64)

Num

ber

ofM

RIa

bno

rmal

ities

0to

4(a

llle

vels

)Pa

in>1

4d

ays

pas

t4

wee

ksYe

s/N

o(?

)22

.2m

onth

s(m

ean)

(74%

)D

isc

deg

ener

atio

n?

(pre

sent

)D

isab

ility

pas

t4

wee

ks(R

M)

0–24

(≥11

poi

nts)

Jens

enet

al.,

2012

96p

atie

nts

ofsp

ecia

list

outp

atie

nt

spin

ecl

inic

46(2

1–60

)M

odic

chan

ges

typ

e1

Yes/

No

(pre

sent

)Pa

in(N

PR

S)0–

10(n

oim

pro

vem

ent,

chan

gesc

ore

≤0)

14m

onth

s(1

00%)

Mod

icch

ange

sty

pe

1(c

hang

ein

size

)

Size

0–4

(incr

ease

)

Klei

nstu

cket

al.,

2006

53p

artic

ipan

tsre

crui

ted

from

loca

lmed

iaad

vert

isem

ents

44(?

)H

igh

inte

nsity

zone

Yes/

No

(pre

sent

)Pa

inla

st2

wee

ks(V

AS)

0–10

(NA

)12

mon

ths

(90%

)

Dis

cb

ulge

Yes/

No

(pre

sent

)D

isab

ility

(RM

)0–

24(N

A)

Dis

cd

egen

erat

ion

Gra

ded

5–25

(>16

)

Mod

icch

ange

typ

e1

and

typ

e2

Gra

ded

0–15

(?)

Mod

icet

al.,

2005

246

pat

ient

sno

n-re

spon

der

sto

a

pre

oper

ativ

ein

tens

ive

cons

erva

tive

in-/o

utp

atie

nt

trea

tmen

tp

rogr

amm

e

43(?

)C

anal

sten

osis

?(p

rese

nt)

Dis

abili

ty(R

M)

0–24

(<50

%im

pro

vem

ent)

24m

onth

s(8

0%)

Ner

vero

otco

mp

ress

ion

?(p

rese

nt)

Dis

che

rnia

tion

?(p

rese

nt)

Pop

ulat

ions

ofp

eop

lew

ithan

dw

ithou

tcu

rren

tLB

P

Car

rage

eet

al.,

2006

a

200

pat

ient

sfr

omun

iver

sity

hosp

ital

39.4

(?)

Dis

cd

egen

erat

ion

Gra

ded

1–5

(gra

de

≥3)

Pain

(NP

RS)

0–10

(≥6

for

≥1w

eek)

60m

onth

s(1

00%)

End

pla

tech

ange

sM

ildto

seve

re(>

mod

erat

e)

Can

alst

enos

isM

ildto

seve

re(>

mod

erat

e)D

isab

ility

(OD

I)0–

100

(?)

Car

rage

eet

al.,

2005

100

pat

ient

sfr

omun

iver

sity

hosp

ital

42(?

)D

isc

hern

iatio

nYe

s/N

o(p

rese

nt)

Pain

(rem

issi

on)

Yes/

No

(6m

onth

s)63

mon

ths

(mea

n)

(100

%)

Pop

ulat

ion

with

nocu

rren

tLB

P,b

utp

revi

ous

LBP

Jarv

iket

al.,

2005

148

Vet

eran

sA

ffai

rsou

tpat

ient

s54

(36–

71)

Dis

che

rnia

tion

Pro

trus

ion

orex

trus

ion

(pre

sent

)Pa

in(P

FI)

1–6

(pai

n>2

oran

yof

the

othe

rth

ree

sym

pto

ms

as>1

)

36m

onth

s(8

8%)

Ner

vero

otco

ntac

tC

onta

ct/d

evia

tion/

com

pre

ssio

n

(pre

sent

)

Can

alst

enos

isM

ildto

seve

re(>

mod

erat

e)

Pop

ulat

ions

with

nohi

stor

yof

LBP

Elfe

ring

etal

.,

2002

41tr

aum

ap

atie

nts

pre

sent

ing

toa

univ

ersi

tycl

inic

?(2

0–50

)D

isc

deg

ener

atio

n(c

hang

e)Sa

me

orw

orse

(wor

seni

ng)

Pain

(NQ

)D

ays

with

pai

nla

stm

onth

(>8)

62m

onth

s(m

ean)

(100

%)

Boo

set

al.,

2000

46p

atie

nts

ofa

univ

ersi

tycl

inic

?(?)

Dis

che

rnia

tion

Yes/

No

(pre

sent

)Pa

in(N

Q)

Day

sw

ithp

ain

last

mon

th

(>8)

62m

onth

s(m

ean)

(100

%)N

erve

root

cont

act

Con

tact

/dev

iatio

n/co

mp

ress

ion

(pre

sent

)

Dis

cd

egen

erat

ion

Gra

de

1to

5(p

rese

nt)

Bor

enst

ein

etal

.,

2001

67vo

lunt

eers

recr

uite

dth

roug

h

adve

rtis

ing

orb

yw

ord

ofm

onth

42(?

)M

RIa

bno

rmal

ities

(cha

nge)

?(w

orse

ning

)Pa

in(o

rdin

alsc

ale)

0–5

(?)

84m

onth

s(7

5%)

?,no

tre

por

ted

;LB

P,lo

wb

ack

pai

n;M

RI,

mag

netic

reso

nanc

eim

agin

g;N

A,n

otap

plic

able

(con

tinuo

usou

tcom

e);N

PR

S,nu

mer

ical

pai

nra

ting

scal

e;N

Q,N

ord

icq

uest

ionn

aire

;OD

I,O

swes

try

dis

abili

tyq

uest

ionn

aire

;PFI

,pai

nfr

eque

ncy

ind

ex;P

GI-I

,pat

ient

glob

alim

pre

ssio

nof

imp

rove

men

tsc

ale;

RM

,Rol

and

Mor

ris

dis

abili

tyq

uest

ionn

aire

;VA

S,vi

sual

anal

ogue

scor

es.



126

Table 3 Association between presence of MRI findings and poor clinical outcome.

MRI findings present Study Clinical outcome (follow-up duration) OR (95% CI) unless indicated

Populations with current LBPModic changes type 1 Jensen et al., 2012 Pain (14 months) 6.2 (1.9–20.2)Modic changes type 1 (change in size) Jensen et al., 2012 Pain (14 months) 1.0 (0.4–2.4)Modic changes type 1 Keller et al., 2012 Impression of improvement (12 months) 1.1 (0.5–2.7)a

Modic changes type 1 Hellum et al., 2012 Disability (12 months) 1.4 (0.5–4.1)Modic changes type 2 Hellum et al., 2012 Disability (12 months) 0.5 (0.2–1.4)Modic changes type 2 Keller et al., 2012 Impression of improvement (12 months) 1.4 (0.7–2.6)a

Modic changes type 1 or type 2 Hellum et al., 2012 Disability (12 months) 0.3 (0.1–1.6)Modic changes type 1 and type 2 Kleinstuck et al., 2006 Pain (12 months) −2 (p = 0.1)b

Modic changes type 1 and type 2 Hellum et al., 2012 Disability (12 months) 1.0 (0.3–3.3)Modic changes type 1 and type2 Kleinstuck et al., 2006 Disability (12 months) 0.4 (p = 0.2)b

Disc degeneration McNee et al., 2011 Pain (22.2 months, mean) 1.6 (0.9–2.8)Disc degeneration Kleinstuck et al., 2006 Pain (12 months) −1 (p = 0.4)b

Disc degeneration McNee et al., 2011 Disability (22.2 months, mean) 2.2 (1.2–4.0)Disc degeneration Kleinstuck et al., 2006 Disability (12 months) −0.8 (p = 0.1)b

Disc degeneration (height reduction) Hellum et al., 2012 Disability (12 months) 0.7 (0.2–2.1)Disc degeneration (signal intensity) Hellum et al., 2012 Disability (12 months) 0.7 (0.2–3.0)High-intensity zone Kleinstuck et al., 2006 Pain (12 months) −2 (p = 0.1)b

High-intensity zone Hellum et al., 2012 Disability (27 months) 1.5 (0.5–4.5)High-intensity zone Kleinstuck et al., 2006 Disability (12 months) 0.3 (p = 0.5)b

Disc bulge Kleinstuck et al., 2006 Pain (12 months) 1 (p = 0.4)b

Disc bulge Kleinstuck et al., 2006 Disability (12 months) 0.8 (p = 0.1)b

Facet joint arthopathy (≥moderate) Hellum et al., 2012 Disability (27 months) 0.7 (0.2–3.0)Disc herniation Modic et al., 2005 Disability (24 months) 0.4 (0.2–0.7)Canal stenosis Modic et al., 2005 Disability (24 months) 2.4 (0.9–6.7)Nerve root compression Modic et al., 2005 Disability (24 months) 0.8 (0.4–1.5)≥1 MRI abnormality McNee et al., 2011 Pain (22.2 months, mean) 0.7 (0.3–1.6)≥2 MRI abnormalities McNee et al., 2011 Pain (22.2 months, mean) 0.8 (0.4–1.8)≥3 MRI abnormality McNee et al., 2011 Pain(22.2 months, mean) 1.0 (0.4–2.2)≥1 MRI abnormality McNee et al., 2011 Disability (22.2 months, mean) 1.2 (0.5–2.9)≥2 MRI abnormalities McNee et al., 2011 Disability (22.2 months, mean) 1.3 (0.5–3.2)≥3 MRI abnormality McNee et al., 2011 Disability (22.2 months, mean) 1.5 (0.6–3.7)Populations of people with and without current LBPDisc degeneration (grade 5) Carragee et al., 2006a Pain (60 months) 4.4 (p = 0.08)c

Disc degeneration (graded ≥3) Carragee et al., 2006a Disability (60 months) 1.0 (0.4–2.3)Canal stenosis Carragee et al., 2006a Pain (60 months) 2.9 (p = 0.09)c

Canal stenosis (≥moderate) Carragee et al., 2006a Disability (60 months) 2.1 (0.8–5.1)Endplate changes (≥moderate) Carragee et al., 2006a Pain (60 months) 2.5 (p = 0.1)c

Disc herniation Carragee et al., 2005 Pain (63 months, mean) 0.2 (p = 0.01)c

Population with no current LBP, but previous LBPDisc herniation (extrusion) Jarvik et al., 2005 Pain (36 months) 1.2 (0.4–3.4)a

Disc herniation (protrusion) Jarvik et al., 2005 Pain (36 months) 0.5 (0.3–0.9)a

Nerve root contact Jarvik et al., 2005 Pain (36 months) 2.2 (0.6–8.0)a

Canal stenosis (>moderate) Jarvik et al., 2005 Pain (36 months) 1.9 (0.8–4.8)a

Populations with no history of LBPDisc degeneration Boos et al., 2000 Pain (62 months, mean) 2.1 (0.1–26.9)Disc degeneration (change) Elfering et al., 2002 Pain (62 months, mean) 4.8 (0.3–69.3)Disc herniation Boos et al., 2000 Pain (62 months, mean) 0.7 (0.1–9.3)Nerve root contact Boos et al., 2000 Pain (62 months, mean) 8.8 (0.6–117.2)MRI abnormalities (change) Borenstein et al., 2001 Pain (84 months) 3.5d

Odds ratios greater than 1 indicate greater odds of poor outcome in those with MRI feature than those without. LBP, low back pain; MRI, magnetic

resonance imaging.aHazard ratios (95% confidence interval). Hazard ratios greater than 1 indicate greater incidence of outcome in those with MRI feature than those without.

A positive association was defined as CI limits above 1.bβ (p-value) positive values indicate that the presence of the given MRI finding at baseline was associated with a poorer outcome.cOdds ratios (p-value), no confidence interval reported.dRelative risk (no confidence interval provided). Relative risk greater than 1 indicates that the poor outcome is more likely to develop in people with the

MRI feature.



127

3.4.1 Current LBP

Six studies investigated the association between MRIfindings and a range of clinical outcomes in a samplewith current LBP [five with chronic LBP (Kleinstucket al., 2006; McNee et al., 2011; Hellum et al., 2012;Jensen et al., 2012; Keller et al., 2012) and one withacute LBP (Modic et al., 2005)]. Of the six studies, fourreported on associations of Modic changes [type 1(Kleinstuck et al., 2006; Jensen et al., 2012) and/ortype 2 (Kleinstuck et al., 2006; Hellum et al., 2012;Keller et al., 2012)], three on disc degeneration(Kleinstuck et al., 2006; McNee et al., 2011; Hellumet al., 2012), two on high-intensity zone (HIZ)(Kleinstuck et al., 2006; Hellum et al., 2012) and onlyone reported on each of disc bulge (Kleinstuck et al.,2006), disc herniation (Modic et al., 2005), canalstenosis (Modic et al., 2005), facet joint arthropathy(Hellum et al., 2012), the number of MRI abnormali-ties (≥ 1 to ≥ 3) (McNee et al., 2011) and nerve rootcompression (Modic et al., 2005).

The association of Modic changes with LBP(Kleinstuck et al., 2006; Jensen et al., 2012; Kelleret al., 2012) and with disability (Kleinstuck et al.,2006; Hellum et al., 2012; Keller et al., 2012) wasinvestigated by four studies. Jensen et al. (2012)investigated 96 patients recruited from a specializedoutpatient spine clinic. This sample was drawn froman RCT that reported no effect of treatment, andreported a significant association of Modic change type1 with worsening of LBP intensity (OR = 6.2; 95%

CI = 1.9–20.2) over a 14-month period. There was noassociation between the change in size of Modic type 1changes and change in LBP intensity (OR = 1.0; 95%CI = 0.4–2.4), dichotomized into improvement(decrease in LBP intensity) or no improvement (nochange or increase of LBP intensity). Hellum et al.(2012) reported data from a randomized trial con-ducted at five hospitals. One hundred and fifty-fivepatients were randomized to receive either conserva-tive treatment or disc replacement surgery. In the con-servatively treated group (n = 66), neither type 1 ortype 2 Modic changes (OR = 0.3; 95% CI = 0.1–1.6)nor type 1 or type 2 Modic changes (OR = 1.0; 95%CI = 0.3–3.3) were significantly associated with dis-ability. Kleinstuck et al. (2006) investigated a total of53 patients who participated in a randomized clinicaltrial of active therapy for chronic LBP. Baseline end-plate changes (defined as Modic changes type 1 andtype 2) were not significantly associated with painintensity or disability at 12-month follow-up.

Only one study reported recovery rate at follow-up(Keller et al., 2012) in a sample of patients withcurrent LBP (n = 269). After 1 year, 40% of patientsrated themselves as recovered. Neither type 1 Modicchanges [hazard ratio (HR) = 1.1; 95% CI = 0.5–2.7]nor type 2 Modic changes (HR = 1.4; 95% CI = 0.7–2.6) were significantly associated with not recoveringover 12 months.

Disc degeneration was reported in three studies(Kleinstuck et al., 2006; McNee et al., 2011; Hellumet al., 2012). McNee et al. (2011) investigated 323

MRI findings present Outcome (time) MRI+ / -

Outcome+ / -

Odds ratio (95% CI) OR (95% CI)

Modic changes type 1 Jensen et al., 2012 Pain (14 months) 74 / 22 47 / 49 6.2 (1.9–20.2)Modic changes type 1 (change in size) Jensen et al., 2012 Pain (14 months) ? / ? ? / ? 1.0 (0.4–2.4)Modic changes type 1 Hellum et al., 2012 Disability (12 months) 44 / 22 31 / 35 1.4 (0.5–4.1)Modic changes type 2 Hellum et al., 2012 Disability (12 months) 44 / 22 31 / 35 0.5 (0.2–1.4)Modic changes type 1 or 2 Hellum et al., 2012 Disability (12 months) 9 / 59 31 / 37 0.3 (0.1–1.6)Modic changes type 1 and 2 Hellum et al., 2012 Disability (12 months) 53 / 13 30 / 36 1.0 (0.3–3.3)Disc degeneration McNee et al., 2011 Pain (22.2 months, mean) 11 / 13 85 / 155 1.6 (0.9–2.8)Disc degeneration McNee et al., 2011 Disability (22.2 months, mean) 11 / 130 70 / 170 2.2 (1.2–4.0)Disc degeneration (height reduction) Hellum et al., 2012 Disability (12 months) 20 / 45 30 / 35 0.7 (0.2–2.1)Disc degeneration (signal intensity) Hellum et al., 2012 Disability (12months) 10 / 55 30 / 35 0.7 (0.2–3.0)High intensity zone Hellum et al., 2012 Disability (27 months) 42 / 23 30 / 35 1.5 (0.5–4.5)Facet joint arthopathy (≥moderate) Hellum et al., 2012 Disability (27 months) 10 / 55 30 / 35 0.7 (0.2–3.0)Disc herniation Modic et al., 2005 Disability (24 months) ? / ? ? / ? 0.4 (0.2–0.7)Canal stenosis Modic et al., 2005 Disability (24 months) ? / ? ? / ? 2.4 (0.9–6.7)Nerve root compression Modic et al., 2005 Disability (24 months) ? / ? ? / ? 0.8 (0.4–1.5)≥1 MRI abnormality McNee et al., 2011 Pain (22.2 months, mean) 208 / 32 85 / 155 0.7 (0.3–1.6)≥2 MRI abnormalities McNee et al., 2011 Pain (22.2 months, mean) 173 / 32 75 / 130 0.8 (0.4–1.8)≥3 MRI abnormality McNee et al., 2011 Pain (22.2 months, mean) 106 / 32 56 / 82 1.0 (0.4–2.2)≥1 MRI abnormality McNee et al., 2011 Disability (22.2 months, mean) 208 / 32 70 / 170 1.2 (0.5–2.9)≥2 MRI abnormalities McNee et al., 2011 Disability (22.2 months, mean) 173 / 32 61 / 144 1.3 (0.5–3.2)≥3 MRI abnormality McNee et al., 2011 Disability (22.2 months, mean) 106 / 32 44 / 94 1.5 (0.6–3.7)

0.1 0.2 0.5 1 2 5 10

Study

Number of events

Figure 2 Forest plot presenting association

between magnetic resonance imaging (MRI)

findings and low back pain (LBP) outcomes on

a sample with current LBP.

MRI finding present Outcome (time) MRI+ / -

Outcome+ / -

Odds ratio (95% CI) OR (95% CI)

Disc degeneration Boos et al., 2000 Pain (62 months, mean) 15 / 15 3 / 27 2.1 (0.1–26.9)Disc degeneration (change) Elfering et al., 2002 Pain (62 months, mean) 19 / 21 3 / 32 4.8 (0.3–69.3)Disc herniation Boos et al., 2000 Pain (62 months, mean) 22 / 8 3 / 27 0.7 (0.1–9.3)Nerve root contact Boos et al., 2000 Pain (62 months, mean) 7 / 23 3 / 27 8.8 (0.6–117.2)

Sample with mixed LBP

Sample with no history of LBP

Study

Disc degeneration (graded ≥3) Carragee et al, 2006a Pain (60 months) 153 / 47 44 / 156 1.0 (0.4–2.3)Canal stenosis (≥moderate) Carragee et al, 2006a Pain (60 months) 26 / 174 44 / 156 2.1 (0.8–5.1)

0.01 0.1 1 10 100

Number of events

Figure 3 Forest plot presenting association

between magnetic resonance imaging (MRI)

findings and low back pain (LBP) outcomes.



128

patients with mechanical LBP, and found positiveassociations between disc degeneration with LBP(OR = 1.6; 95% CI = 0.9–2.8) and disability (OR = 2.2;95% CI = 1.2–4.0). In the study by Kleinstuck et al.(2006), disc degeneration was not associated withpain, or disability at 12-month follow-up. Hellumet al. (2012) found no association between baselinefindings of disc degeneration (signal intensity) and12-month disability in participants treated conserva-tively (OR = 0.7; 95% CI = 0.2–3.0). Similarly, discdegeneration (height reduction) was not associatedwith 12-month disability (OR = 0.7; 95% CI = 0.2–2.1).

One study investigated the association between thenumber of MRI abnormalities (≥ 1 to ≥ 3) at baselineand future LBP and disability (McNee et al., 2011).Neither one nor more MRI abnormalities were associ-ated with pain or disability at follow-up.

Kleinstuck et al. (2006) found no associationbetween the presence of baseline disc bulge and HIZwith LBP or disability outcomes. Hellum et al. (2012)also investigated the association between HIZ and dis-ability. HIZ in the conservatively treated group(OR = 1.5; 95% CI = 0.5–4.5) was not significantlyassociated with disability at 12 months.

Disc herniation, severe canal stenosis and nerve rootcompression were investigated in one study (Modicet al., 2005). A total of 246 patients were randomizedto either the early information arm of the study, withMRI results provided within 48 h, or the second armof the study, where both patients and physicians wereblinded to MRI results. Disability at 24-monthfollow-up occurred 0.4 times (95% CI = 0.2–0.7) asoften among patients with disc herniation at baselineas among patients without disc herniation. Severecanal stenosis (OR = 2.4; 95% CI = 0.9–6.7) and nerveroot compression (OR = 0.8; 95% CI = 0.4–1.5) werenot significant predictors of future disability.

Similarly, Hellum et al. (2012) reported that base-line findings of facet joint arthropathy did not predictdisability at 12 months (OR = 0.7; 95% CI = 0.2–3.0)in the conservatively treated group.

3.4.2 Mixed samples (sample with and withoutcurrent LBP)

Two studies investigated a mixed sample (subjectswithout or mild LBP symptoms and/or with chronicnon-lumbar pain), reporting associations between discdegeneration, endplate changes, canal stenosis(Carragee et al., 2006a) and disc herniation (Carrageeet al., 2005) with disability (Carragee et al., 2006a)and LBP (Carragee et al., 2005, 2006a) outcomes.

Carragee et al. (2006a) investigated 200 patientsfrom a University Hospital and found that none of thebaseline MRI findings significantly predicted seriousLBP episodes nor disability after 60 months. Grade 5disc degeneration (OR = 4.40; p = 0.08), moderate/severe endplate changes (OR = 2.5; p = 0.1) and canalstenosis (OR = 2.9; p = 0.09) were weakly, but not sig-nificantly, associated with serious LBP episodes.Another study by Carragee et al. (2005) reported thatthe presence of disc herniation was associated withpain (OR = 0.2; p = 0.01) at follow-up, in 100 patientsfrom a University Hospital.

3.4.3 No current LBP, but previous LBP

One study investigated the association between base-line MRI findings and LBP in 128 Veterans Affairspatients who were initially asymptomatic (Jarviket al., 2005). Baseline MRI findings of nerve rootcontact (HR = 2.2; 95% CI = 0.6–8.0) and centralspinal stenosis (HR = 1.9; 95% CI = 0.8–4.8) producednon-significant HRs for future new LBP. The studyfound that having a disc herniation (protrusion)(HR = 0.5; 95% CI = 0.3–0.9) reduced the likelihoodof future LBP, whereas a disc herniation (extrusion)(HR = 1.2; 95% CI = 0.4–3.4) did not predict futurenew LBP episodes.

3.4.4 No history of LBP

Three studies provided estimates of the associationbetween MRI findings [disc degeneration (Boos et al.,2000; Elfering et al., 2002), disc herniation (Booset al., 2000), neural compromise (Boos et al., 2000)and worsening abnormalities on MRI (Borensteinet al., 2001)] with future LBP in a sample of asymp-tomatic individuals with no history of LBP.

Borenstein et al. (2001) followed up 50 subjects for84 months and reported a relative risk that LBP woulddevelop in individuals with worsening abnormalitieson MRI scans of 3.5 (no CIs or p-values reported).

Disc degeneration was investigated by two studies.Elfering et al. (2002) reported the association betweendisc degeneration and LBP after 60 months in 41patients. There was no significant association with LBPin those with disc degeneration (OR = 4.8; 95%CI = 0.3–69.3), although the very wide CIs indicatelack of statistical power. Boos et al. (2000) investigated46 asymptomatic individuals and did not find a signifi-cant association between disc degeneration and LBP(OR = 2.1; 95% CI = 0.1–26.9). Similarly, disc hernia-tion and neural compromise were not predictors of



129

LBP (OR = 0.7; 95% CI = 0.1–9.3 and OR = 8.8; 95%CI = 0.6–117.2, respectively).

4. Discussion

4.1 Statement of principal findings

Twelve studies met the inclusion criteria and wereincluded. Six studies investigated participants withcurrent LBP, two investigated mixed samples includingpeople with and without LBP, one included a samplewith no current LBP, but previous LBP symptoms, andthree studies included a sample of participants with nohistory of LBP. No consistent associations were iden-tified across multiple studies. Single studies reportedsignificant associations for Modic changes type 1(OR = 6.2; 95% CI = 1.9–20.2) with pain, and discdegeneration with disability (OR = 2.2; 95% CI = 1.2–4.0) in samples with current LBP, and disc herniation(OR = 0.2; p = 0.01) with pain in a mixed sample withand without LBP.

This systematic review reveals that there are rela-tively few studies that have investigated MRI findingsas predictors of future LBP. Not only are there fewstudies, but these studies are mostly small (number ofparticipants ranging from 41 to 323) and investigatedifferent MRI findings in a range of different samples(i.e., current LBP, no current LBP or mixed) and usedifferent outcome measures. As a result, it is not pos-sible to draw firm conclusions about the ability of MRIfindings to predict future LBP. Some MRI findingswere statistically associated with future LBP in singlestudies, but comparable studies were not identified toenable confirmation of these findings. The smallsample size of most studies meant that some poten-tially clinically important associations may have beenmissed. It remains unclear whether the MRI findingshave important associations with LBP outcomes orwhether no important associations truly exist.

4.2 Strengths and weaknesses of the study

To our knowledge, this is the first systematic review tosummarize the available evidence of MRI findings pre-dicting future LBP. We used a very sensitive searchstrategy previously used in other high-quality LBPprognosis studies (Pengel et al., 2003; Costa et al.,2012) and MRI systematic reviews (Chou et al., 2011;Endean et al., 2011), making it very likely that alleligible studies were included in our review. We alsoconsulted experts in the field to reduce the risk ofmissing any important articles. A limitation of thepresent study is the heterogeneity of the studies

reviewed particularly the different samples, MRI find-ings investigated and clinical outcomes. For thisreason, we were unable to pool study results. Somestudies included participants from RCTs (Modic et al.,2005; Kleinstuck et al., 2006; Hellum et al., 2012;Jensen et al., 2012) and it is not possible to determinehow the interventions may have impacted on the out-comes. The association between MRI finding andoutcome may vary as a result of confounding due totreatment. The association between MRI findings andoutcomes in a sample that underwent surgery(Hellum et al., 2012) were not reported in this review.Another factor that could have influenced the resultsof the included studies was that most studies used adifferent MRI protocol, sequences and training of MRIreaders. The current review only investigated MRIfindings and does not provide evidence on the value ofplain radiographs or computed tomography scans inpredicting future LBP.

4.3 Comparison with other studies

One previous systematic review has investigated thecross-sectional association of vertebral endplate signalchanges (Modic changes) with current NSLBP (Jensenet al., 2008). A relatively strong association betweenvertebral signal changes and NSLBP was found in 7 of10 studies with ORs ranging from 2.0 to 19.9. In oursearch, we chose to include articles that investigatedthe association of a variety of baseline MRI findings(i.e., disc degeneration, HIZ, herniation) with pain anddisability outcomes in a range of different samples.Furthermore, despite other systematic reviews in thisfield including cross-sectional studies, we chose toexclude these studies as they cannot logically deter-mine if baseline MRI findings predict future LBP.

4.4 Meaning of the study

While single studies reported significant associationsfor Modic changes type 1, disc herniation and discdegeneration for future LBP, there remains consider-able uncertainty about the importance of MRI find-ings. Definitive conclusions are not possible as theavailable studies typically enrolled small non-representative samples and the results were inconsis-tent between studies. Perhaps the only clear result toemerge from this review is that there is a paucity ofhigh-quality studies in this important area. Thisabsence of evidence is in contrast with the rapidlyincreasing use of MRI in patients with LBP (Chouet al., 2012).



130

Many of the MRI findings are truly continuous mea-sures with different degrees of severity. Despite this,included studies tend to dichotomize these (i.e.,present or no present). This may result in loss ofimportant data, and therefore, more research isneeded to investigate if the relationships are linear orif important thresholds exist.

4.5 Recommendations for future research

Further large, high-quality studies are clearly neededto help determine the clinical meaningfulness of MRIfindings in relation to LBP. Additionally, a number offactors related to reporting of included studies could beimproved. Firstly, all of the included studies had somemethodological shortcomings. Future studies shoulddescribe the selection of participants in more detail.Assessment and reporting of clinical outcomes was notwell standardized. For example, pain intensity wasmeasured in nine studies with four different scales.Standardized methods for reporting outcomes, basedon published recommendations, would greatlyimprove future studies (Bombardier, 2000). The use ofa standardized MRI protocol, same sequences andtraining of MRI readers is also highly recommended.

The investigation of association between MRI find-ings and clinical outcomes is complicated. All reviewedstudies focused on the association between a singleimaging findings and pain and/or disability. Futurestudies should investigate which MRI findings typicallyoccur together and whether clusters of findings aremore predictive of outcome than single findings.

5. Conclusion

This review shows that there are few (heterogeneous)longitudinal studies that have investigated the associa-tion of lumbar spine MRI findings and LBP outcomes,which indicates the need for further research.

Acknowledgement

We thank Prof Jeffrey Jarvik for reviewing included studiesand suggesting possible additional studies.

Author contributions

D.S. designed and managed the study, planned analysis,drafted manuscript, extracted and analysed data. M.J.H.designed and managed the study, planned analysis, extractedand analysed data. C.G.M. designed and managed the study,extracted data and edited the manuscript. C.W., T.S.J. and

J.L. designed the study, extracted data and edited the manu-script. All authors approved the final version.

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Supporting Information

Additional Supporting Information may be found in theonline version of this article at the publisher’s web-site:

Appendix S1. Search strategy.Appendix S2. List of excluded full-text articles and theprimary reason for exclusion.



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Appendix S1. Search strategy

MEDLINE1 exp cohort studies/2 incidence/3 follow-up studies.mp.4 prognos$.mp.5 predict$.mp.6 course.mp.7 inception.mp.8 survival.mp.9 logistic.mp.

10 Cox.mp.11 life tables.mp.12 log rank.mp.13 or/1–1214 low back pain.mp.15 back pain.mp.16 Lumbago.mp.17 Back injuries.mp.18 Backache.mp.19 or/14–1820 Magnetic resonance Imaging/21 MRI.mp.22 Magnetic adj5 resonance.mp.23 NMR.mp.24 Nuclear magnetic resonance.mp.25 Disc degeneration.mp.26 Desiccation.mp.27 Loss of disc height.mp.28 Bulge.mp.29 Protrusion.mp.30 Extrusion.mp.31 Nerve root compromise.mp.32 Annular tear.mp.33 Endplate changes.mp.34 Stenosis.mp.35 Facet degeneration.mp.36 High intensity zone.mp.37 Modic changes.mp.38 Degenerative disc disease.mp.39 Spondylolisthesis.mp.40 or/20–3941 13 AND 19 AND 40EMBASE

1 (‘cohort analysis’/exp AND [embase]/lim)2 (‘incidence’/exp AND [embase]/lim)3 (‘follow up’/exp OR ‘follow up’ AND [embase]/lim)4 (‘prognosis’/exp OR prognos* AND [embase]/lim)5 (‘prediction’/exp OR predict* AND [embase]/lim)6 (‘disease course’/exp OR ‘course’ AND [embase]/lim)7 (‘inception’/exp AND [embase]/lim)8 (‘survival’/exp OR ‘survival’ AND [embase]/lim)9 (‘logistic regression analysis’/exp OR ‘logistic’ AND

[embase]/lim)10 (‘proportional hazards model’/exp OR ‘cox’ AND [embase]/lim)11 (‘life table’/exp OR ‘life table’ OR ‘life tables’/exp OR ‘life tables’ AND

[embase]/lim)12 (‘log rank test’/exp OR ‘log rank’ AND [embase]/lim)13 1 or 2 or 3 or 4 or 5 or 6 or 7 or 8 or 9 or 10 or 11 or 1214 (‘low back pain’/exp OR ‘low back pain’ AND [embase]/lim)15 (‘backache’/exp OR ‘low back pain’/exp AND [embase]/lim)16 (‘Lumbago’/exp AND [embase]/lim)17 (‘Back injuries’/exp AND [embase]/lim)18 14 or 15 or 16 or 17

19 13 AND 1820 (‘Magnetic resonance Imaging’/exp AND [embase]/lim)21 (‘MRI’/exp AND [embase]/lim)22 (‘Magnetic resonance’/exp AND [embase]/lim)23 (‘NMR’/exp AND [embase]/lim)24 (‘Nuclear magnetic resonance’/exp AND [embase]/lim)25 (‘Disc degeneration’/exp AND [embase]/lim)26 (‘Desiccation’/exp AND [embase]/lim)27 (‘Loss of disc height’/exp AND [embase]/lim)28 (‘Bulge’/exp AND [embase]/lim)29 (‘Protrusion’/exp AND [embase]/lim)30 (‘Extrusion’/exp AND [embase]/lim)31 (‘Nerve root compromise’/exp AND [embase]/lim)32 (‘Annular tear’/exp AND [embase]/lim)33 (‘Endplate changes’/exp AND [embase]/lim)34 (‘Stenosis’/exp AND [embase]/lim)35 (‘Facet degeneration’/exp AND [embase]/lim)36 (‘High intensity zone’/exp AND [embase]/lim)37 (‘Modic changes’/exp AND [embase]/lim)38 (‘Degenerative disc disease’/exp AND [embase]/lim)39 (‘Spondylolisthesis’/exp AND [embase]/lim)40 20 or 21 or 22 or 23 or 24 or 25 or 26 or 27 or 28 or 29 or 30 or 31

or 31 or 33 or 34 or 35 or 36 or 37 or 38 or 39 or 4019 AND 40

CINAHL1 (MH ‘Prospective Studies+’)2 (MH ‘incidence+’)3 ‘predic*’4 (MH ‘prognosis+’)5 ‘course’6 ‘Inception’7 (MH ‘Survival Analisis+’) or (MH ‘Cox Proportional Hazards Model’)8 (MH ‘Logistic Regression+’)9 (MH ‘Life Table Methods’)

10 (MH ‘Log-Rank Test’)11 1 or 2 or 3 or 4 or 5 or 6 or 7 or 8 or 9 or 1012 (MH ‘Low Back Pain’) or (MH ‘Back Pain+’)13 (MH ‘Lumbago+’)14 (‘Back injuries+’)15 (‘Backache+’)16 12 or 13 or 14 or 1517 11 AND 1618 (MH ‘MRI’) or (MH ‘Magnetic Resonance’)19 (MH ‘NRI’) or (MH ‘Nuclear Magnetic Resonance’)20 (MH ‘Disc degeneration+’)21 (MH ‘Desiccation+’)22 (MH ‘Loss of disc heigh+’)23 (MH ‘Bulge+’)24 (MH ‘Protrusion+’)25 (MH ‘Extrusion+’)26 (MH ‘Nerve root compromise+’)27 (MH ‘Annular tear+’)28 (MH ‘Endplate changes+’)29 (MH ‘Stenosis+’)30 (MH ‘Facet degeneration+’)31 (MH ‘High intensity zone+’)32 (MH ‘Modic changes+’)33 (MH ‘Degenerative disc disease+’)34 (MH ‘Spondylolisthesis+’)35 18 or 19 or 20 or 21 or 22 or 23 or 24 or 25 or 26 or 27 or 28 or 29

or 30 or 31 or 32 or 33 or 3436 17 AND 35

133

Appendix S2. List of excluded full-text articles and the primary reason forexclusion

# Study Title First reason for excluding

#1 Albert, H. B. et al. 2007 Modic changes following lumbar disc herniation No association

#2 Ash, L. M. et al. 2008 Effects of diagnostic information, per se, on patient outcomes in acute radiculopathy

and low back pain

No LBP outcome at

follow-up

#3 Baranto, A. et al. 2006 Back pain and degenerative abnormalities in the spine of young elite divers: A 5-year

follow-up magnetic resonance imaging study

No LBP outcome at

follow-up

#4 Baranto, A., M. et al. 2009 Back pain and MRI changes in the thoraco-lumbar spine of top athletes in four different

sports: A 15-year follow-up study

No LBP outcome at

follow-up

#5 Bartolozzi, C. et al. 1991 The incidence of disk changes in volleyball players. The magnetic resonance findings Not a prospective study

#6 Beattie, P. F. et al. 2000 Associations between patient report of symptoms and anatomic impairment visible on

lumbar magnetic resonance imaging

Not a prospective study

#7 Bennett, A. N. et al. 2008 Severity of baseline magnetic resonance imaging-evident sacroiliitis and HLA-B27

status in early inflammatory back pain predict radiographically evident ankylosing

spondylitis at eight years

No association

#8 Bennett, D. L. et al. 2006 Lumbar spine MRI in the elite-level female gymnast with low back pain No LBP outcome at

follow-up

#9 Boden, S. D. et al. 1990 Abnormal magnetic-resonance scans of the lumbar spine in asymptomatic subjects. A

prospective investigation

No LBP outcome at

follow-up

#10 Borthakur, A. et al. 2011 T1(rho) magnetic resonance imaging and discography pressure as novel biomarkers for

disc degeneration and low back pain


#11 Braithwaite, I. et al. 1998 Vertebral endplate (Modic) changes on lumbar spine MRI: correlation with pain

reproduction at lumbar discography


#12 Buirski, G. 1992 Magnetic resonance signal patterns of lumbar discs in patients with low back pain. A

prospective study with discographic correlation


#13 Buirski, G. and M.

Silberstein 1993

The symptomatic lumbar disc in patients with low-back pain. Magnetic resonance

imaging appearances in both a symptomatic and control population


#14 Buttermann, G. R. et al.

2008

Pain and disability correlated with disc degeneration via magnetic resonance imaging

in scoliosis patients


#15 Buttermann, G.R. 2004 The effect of spinal steroid injections for degenerative disc disease No association

#16 Carragee, E. J. et al. 2000 2000 Volvo Award winner in clinical studies: Lumbar high-intensity zone and

discography in subjects without low back problem.


#17 Carragee, E. J. et al. 2004 Prospective controlled study of the development of lower back pain in previously

asymptomatic subjects undergoing experimental discography

No association

#18 Chen, B., et al. 2001 The magnetic resonance imaging of the lumbar spine in out-patients with low back

pain


#19 Cheung, K. M. et al. 2009 Prevalence and pattern of lumbar magnetic resonance imaging changes in a

population study of one thousand forty-three individuals


#20 de Schepper, E. I. et al.

2010

The association between lumbar disc degeneration and low back pain: the influence of

age, gender, and individual radiographic features


#21 Erkintalo, M. O. et al. 1995 Development of degenerative changes in the lumbar intervertebral disk: Results of a

prospective MR imaging study in adolescents with and without low-back pain

No association

#22 Esposito, P. et al 2006 Predictive value of MRI vertebral end-plate signal changes (Modic) on outcome of

surgically treated degenerative disc disease. Results of a cohort study including 60

patients

No LBP outcome at

follow-up

#23 Fayad, F. et al. 2007 Relation of inflammatory modic changes to intradiscal steroid injection outcome in

chronic low back pain


#24 Fayad, F. et al. 2009 Reliability of a modified Modic classification of bone marrow changes in lumbar spine

MRI.


#25 Grable, H. R. 1993 Abnormal findings on magnetic resonance imaging in a group of motor vehicle

accident patients with low back pain


#26 Graves, J. M. et al. 2012 Early imaging for acute low back pain: One-year health and disability outcomes among

Washington state workers

No MRI at baseline

#27 Haig, A. J. et al. 2006 Predictors of pain and function in persons with spinal stenosis, low back pain, and no

back pain


#28 Hollingworth, W. et al.

1998

Self reported health status and magnetic resonance imaging findings in patients with

low back pain

No association

134

Appendix S2. (continued)

# Study Title First reason for excluding

#29 Iwamoto, J. et al. 2005 Relationship between radiographic abnormalities of lumbar spine and incidence of low

back pain in high school rugby players: A prospective study

No MRI at Baseline

#30 Jensen, O. K. et al. 2010 One-year prognosis in sick-listed low back pain patients with and without radiculopathy.

Prognostic factors influencing pain and disability

No MRI at Baseline

#31 Jensen, R.K. et al 2011 Is the presence of Modic changes associated with the outcomes of different

treatments? A systematic critical review


#32 Jensen, T. S. et al. 2009 Characteristics and natural course of vertebral endplate signal (Modic) changes in the

Danish general population

No LBP outcome at

follow-up

#33 Jensen, T. S. et al. 2010 Predictors of new vertebral endplate signal (Modic) changes in the general population No LBP outcome at

follow-up

#34 Jensen, T.S. et al 2007 Magnetic resonance imaging findings as predictors of clinical outcome in patients with

sciatica receiving active conservative treatment

No LBP outcome at

follow-up

#35 Kanayama, M. et al. 2009 Cross-sectional magnetic resonance imaging study of lumbar disc degeneration in 200

healthy individuals: Clinical article


#36 Kerttula, L. et al. 2012 Modic type I change may predict rapid progressive, deforming disc degeneration: a

prospective 1-year follow-up study

No LBP outcome at

follow-up

#37 Kuisma, M. et al 2006 A three-year follow-up of lumbar spine endplate (Modic) changes No LBP outcome at

follow-up

#38 Kujala, U. M. et al. 1996 Low-back pain in adolescent athletes No LBP outcome at

follow-up

#39 Kujala, U. M. et al. 1999 Prolonged low-back pain in young athletes: a prospective case series study of findings

and prognosis

No association

#40 Luoma, K. et al. 2008 MRI follow-up of subchondral signal abnormalities in a selected group of chronic low

back pain patients


#41 Luoma, K. et al. 2009 Relationship of Modic type 1 change with disc degeneration: A prospective MRI study No LBP outcome at

follow-up

#42 Marzo-Ortega, H. et al.

2009

Baseline and 1-year magnetic resonance imaging of the sacroiliac joint and lumbar

spine in very early inflammatory back pain. Relationship between symptoms,

HLA-B27 and disease extent and persistence

No LBP outcome at

follow-up

#43 Matsui, H. et al. 1998 Familial predisposition for lumbar degenerative disc disease Not a prospective study

#44 Mitra, D. et al. 2004 Longitudinal study of vertebral type-1 end-plate changes on MR of the lumbar spine Not a prospective study

#45 Siepe, C.J. et al 2006 Clinical results of total lumbar disc replacement with prodisc II No association

#46 Symmons, D. P. et al.

1991

A longitudinal study of back pain and radiological changes in the lumbar spines of

middle aged women. II. Radiographic findings

No MRI at Baseline

#47 Takatalo, J. et al. 2011 Does lumbar disc degeneration on magnetic resonance imaging associate with low

back symptom severity in young Finnish adults?


#48 Tung, G. A. et al. 1999 Spinal epidural abscess: Correlation between MRI findings and outcome Not a prospective study

#49 Videman, T. et al. 2003 Associations between back pain history and lumbar MRI findings Not a prospective study

#50 Waris, E. et al. 2007 Disc degeneration in low back pain: a 17-year follow-up study using magnetic

resonance imaging

No LBP outcome at

follow-up

#51 Williams, F. M. K. et al.

2011

Progression of lumbar disc degeneration over a decade: A heritability study No LBP outcome at

follow-up

135

Chapter Seven

Prognosis of chronic low back pain in patients presenting to a private community-

based group exercise program

Chapter Seven is published as:

Steffens D, Hancock MJ, Maher CG, Latimer J, Satchell R, Ferreira ML, Ferreira PH,

Partington M, Bouvier AL. Prognosis of chronic low back pain in patients presenting to a

private community-based group exercise program. European Spine Journal. 2014; 23: 113-

119.

136


As co-authors of the paper “Prognosis of chronic low back pain in patients presenting to a

private community-based group exercise program”, we confirm that Daniel Steffens has

made the following contributions:


Data collection






Rob Satchell Date: 01.01.2015



Melissa Partington Date: 01.01.2015

Anna L Bouvier Date: 01.01.2015

137

ORIGINAL ARTICLE

Prognosis of chronic low back pain in patients presentingto a private community-based group exercise program

Daniel Steffens • Mark J. Hancock • Chris G. Maher • Jane Latimer •

Robert Satchell • Manuela Ferreira • Paulo H. Ferreira • Melissa Partington •

Anna-Louise Bouvier

Received: 10 October 2012 / Revised: 8 May 2013 / Accepted: 1 June 2013 / Published online: 23 June 2013

� Springer-Verlag Berlin Heidelberg 2013

Abstract

Purpose To examine the prognosis and prognostic factors

for patients with chronic low back pain presenting to a

private, community-based, group exercise program.

Methods A total of 118 consecutive patients with chronic

LBP were recruited. Baseline assessments included socio-

demographic characteristics, back pain history and clinical

examination findings. Primary outcome measures were pain

intensity and disability at 3, 6 and 12 months. Potential

prognostic factors to predict pain intensity and disability at

12 months were assessed using a multivariate regression

model.

Results 112 (95 %) participants were followed up at

12 months. The majority of participants were female

(73 %), had high educational levels (82 %) and resided in

suburbs with a high socio-economic status (99 %). Pain

intensity improved markedly during the first 6 months

(35 %) with further minimal reductions up to 12 months

(39 %). Interestingly, disability improved to a greater

degree than pain (48 % improvement at 6 months) and

continued to improve throughout the 12 months (60 %).

Baseline pain intensity accounted for 10 % of the variance

in the 1 year pain outcomes. Duration of current episode,

baseline disability and educational level accounted for

15 % of the variation in disability at 12 months.

Conclusions During a period of 12 months, patients with

chronic LBP presenting to a private, community-based,

group exercise program improved markedly, with greater

improvements in disability than pain. The predictors

investigated accounted for only 10 and 15 % of pain and

disability outcomes, respectively.

Keywords Chronic low back pain � Prognosis �Disability �Outcomes

Introduction

Clinical guidelines report the prognosis of chronic back

pain to be poor [1]. A recent systematic review of the

course of acute and chronic LBP [2] found moderate

within-study and between-study variability in both pain

and disability outcomes. This strongly suggests that while

the average prognosis may be poor this is not the case for a

substantial proportion of people. The moderate levels of

between-study variability suggest that factors related to

study design, setting and participants may significantly

impact on the reported prognoses.

Previous studies have identified factors associated with

prognosis in chronic LBP [3–6]; however, the lack of

quality studies means prognostic factors for chronic LBP

D. Steffens (&) � C. G. Maher � J. Latimer � M. Ferreira


Health, University of Sydney, Level 13, 321 Kent Street,


e-mail: [email protected]

M. J. Hancock

Discipline of Physiotherapy, Faculty of Human Sciences,

Macquarie University, 2 Technology Place, Macquarie Park,


R. Satchell

Coast Allied Health, 2/171 Prince Edward Ave,

Culburra Beach, NSW 2540, Australia

P. H. Ferreira

Discipline of Physiotherapy, Faculty of Health Sciences,

The University of Sydney, Lidcombe,


M. Partington � A.-L. Bouvier

Physiocise, Movement for Life, Suite 14, 77 Penshurst Street,

Willoughby, Sydney, NSW 2068, Australia

123

Eur Spine J (2014) 23:113–119

DOI 10.1007/s00586-013-2846-x

138

remain unclear [7]. A large Australian cohort study [8]

found previous sick leave due to LBP, high disability levels

or high pain intensity at onset of chronicity, low levels of

education, greater perceived risk of persistent pain, and

being born outside Australia (immigrants) were associated

with delayed recovery. Patients presenting for care in set-

tings where these adverse prognostic factors are uncommon

may have a more favorable prognosis than widely reported.

Until now no study has investigated the prognosis of

people with chronic low back pain attending a private,

community-based, group exercise program.

It is reasonable to expect that evidence-based treatments

which are endorsed in clinical guidelines will impact on the

prognosis reported and may be an important source of the

between-study variability [2]. The European guideline for

the management of chronic non-specific LBP recommends

supervised exercise therapy as a first-line treatment in the

management of chronic LBP. Furthermore, group exercise

and the use of cognitive behavioral therapy are also rec-

ommended [1]. Community-based group exercise programs

based on guideline recommendations for chronic LBP have

become increasingly common in the management of

chronic LBP. Many of these programs are private, and

given the requirement that patients must pay for the ser-

vice, attract patients without work related injuries with

higher average socioeconomic status and level of educa-

tion. However, the prognosis of this particular group of

private paying patients presenting to individualized group

exercise classes is not well reported in the literature.

In assessing the prognosis of chronic LBP it is important

to consider at a minimum both pain and disability out-

comes. A recent review found greater changes in pain than

disability but lower absolute scores for disability than pain

at 1 year, as the baseline pain levels were higher than

disability [2]. A better understanding of the relative prog-

nosis in terms of pain and disability for people paying for

and receiving high quality group exercise programs is

important. Therefore, the aim of the present study was to

examine the prognosis and prognostic factors for private

paying patients with chronic LBP who presented to a pri-

vate, community-based, group exercise program.

Materials and methods

We conducted a prospective study of participants with

chronic LBP presenting to a private, community-based,

group exercise program.

Setting and participants

Consecutive patients with LBP who presented to a private,

community-based, group exercise program were invited to

participate if they met all the following inclusion criteria;

(1) chronic non-specific LBP (symptoms greater than

3 months duration, according to the classification proposed

by de Vet et al. [4]) with or without leg pain (2) pain on a

numerical pain rating scale equal or greater than two out of

ten (3) adequate English communication for all data to be

recorded and (4) baseline assessment performed less than

4 weeks prior to exercise classes starting. Exclusion cri-

teria were (1) LBP that was not attributable to a recog-

nizable, known specific pathology (e.g., infection, tumor,

fracture, inflammatory disorder, cauda equina, radicular

syndrome) [1], or (2) nerve root compromise (with at least

two of the following signs: myotomal weakness, derma-

tomal sensory loss or hyporeflexia of the lower limb) or (3)

currently pregnant. The University of Sydney’s Human

Research Ethics Committee approved the study.

Baseline data collection

Baseline data were collected by a physiotherapist as part of

the standard 90-min assessment for all patients prior to

starting the group exercise program. Data collected inclu-

ded demographic information, baseline measures of out-

comes and potential prognostic factors.

Group exercise program

All participants were enrolled in a group exercise program,

at one of two private clinics in Sydney. The program

involved a strong educational component combined with

physical retraining. Patients paid up front for a 10 week

foundation program. Patients with private health insurance

(87 %) were able to claim up to 50 % of the total cost of

the classes from their insurer. The foundation program

focuses on movement and posture re-education, combined

with very specific pain behavior education, Acceptance and

Commitment Therapy principles (focusing on awareness,

acceptance, defusing of negative thoughts) [9] and CBT

specifically in the area of decreasing catastrophizing.

Educational and physical elements of the program focused

on practicing activities of daily living, in particular sitting,

standing, walking and bending. These were performed in

front of large mirrors which gave patients maximum visual

feedback about their physical movement patterns compared

to an idealized goal (e.g., using neutral spine and hip and

knee flexion for bending). The environment was light, non-

threatening, interactive and involved music as well as

education. Participants were also given a book of exercises

and educational materials related to back pain and posture

[10, 11]. At the end of the 10-week program, some par-

ticipants enrolled in more advanced classes while other

participants ceased participation in the group exercise

classes. Advanced classes focused on physical aspects such

114 Eur Spine J (2014) 23:113–119

123

139

as developing lumbo-pelvic stability, endurance with glu-

teal strength, and incorporating upper body strengthening

in functional positions. Whether participants continued in

classes was recorded, but did not impact on their

involvement in the study.

Outcome variables

Outcome measures were assessed at baseline, 3, 6 and

12 months. Follow-up measures were collected when

patients attended the exercise classes. Participants who did

not attend the classes during the week their follow-up

assessment was due, were contacted by telephone and a

telephone interview was conducted by a trained researcher.

Primary outcomes

The primary outcomes were average pain over the past

week measured using the numerical pain rating scale [12]

scored from 0 (no pain) to 10 (worst pain possible) and

disability, measured using the Roland Morris Disability

Questionnaire [13], scored from 0 to 24, with higher scores

indicating worse disability status. Pain was assessed as

both change in pain and also the proportion of patients who

fully recovered from pain (score 0 or 1 for 1 month at time

of assessment).

Secondary outcomes

Secondary outcomes were global impression of recovery

(Global Perceived Effect Scale) [12, 14], bothersomeness

of pain (Bothersome of Pain Scale) [15], function (Patient-

specific Functional Scale) [16] and kinesiophobia (TAMPA

Scale for Kinesiophobia) [17].

Prognostic factors

A limited number of baseline prognostic factors were

investigated. We limited the number of prognostic factors

to one per ten patients [18]. The prognostic factors were

measures of pain intensity, previous episodes of LBP,

duration of current episode, disability, global perceived

effect of improvement, function, kinesiophobia, educa-

tional level, location of pain (absence of pain below the

knee), catastrophizing, patients enrolled to the second term

(scored as 0 = patients that only attended the first term of

the classes or 1 = patients that attended two or more

terms) and an 11-point prognosis scale. The Physiocise

prognosis scale consists of ten items and is scored by

adding up the number of positive items. The score can

therefore vary from 0 to 10 with higher values indicating

worse prognosis. The items are (1) greater than 5 years

since first acute episode; (2) other painful areas, for

instance neck/shoulders; (3) CT/MRI/disc bulges/degener-

ative changes on X-Ray; (4) high kinesiophobia (defined as

scores [40 on the TAMPA Scale for Kinesiophobia); (5)

poor response to hands-on treatment in the last few years;

(6) degree of constant pain (scored as yes/no); (7) unable

to perform certain physical activities because of pain;

(8) difficulty standing for prolonged periods; (9) difficulty

sitting for prolonged periods; (10) trauma, such as

MVA/fall.

Statistical analysis

Analyses were performed using SPSS version 20 (SPSS,

Inc., Chicago, IL). Descriptive statistics (mean ± SD)

were used to summarize the baseline characteristics of the

patients and prognostic outcomes at baseline, 3, 6 and

12 months. Comparison between mean baseline and 3, 6 or

12 month outcomes were performed using Paired–samples

t test. P \ 0.05 was considered significant.

To evaluate prognostic factors, univariate associations

between each of the prognostic variables and pain scores

and disability (RMDQ) at 12 months were assessed using

linear regression. Variables with significant univariate

associations (p \ 0.2) were entered into a backwards

multivariate regression model.

For the regression analyses, the number of previous

episodes was dichotomized (0–1 episodes/2 or more epi-

sodes), duration of the current episode was recorded in

days and log transformed, and educational level was

dichotomized (0 = school, high school certificate and

trade/diploma and 1 = advanced diploma, bachelor degree

and postgraduate degree).

Results

From January 2010 to January 2011 consecutive patients

from two private physiotherapy clinics in Sydney, Aus-

tralia were screened. One hundred and eighteen met the

inclusion criteria and all consented to enter the study.

Follow-up rates were high, with 116 (98 %), 114 (97 %)

and 112 (95 %) participants being followed up at 3, 6

and 12 months, respectively. Baseline characteristics of

the 118 participants are shown in Table 1. The majority

of participants were female (73 %), had high educational

levels (82 %), did not smoke (96 %) and resided in

suburbs with a high socioeconomic status (99 %). All

participants were private paying and not covered by

workers compensation.

Participants’ outcome data at baseline, 3, 6 and

12 months are presented in Table 2 and Fig. 1. Pain

intensity, bothersomeness, disability and function reduced

during the follow-up period, with mean pain intensity,

Eur Spine J (2014) 23:113–119 115

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bothersomeness, disability and function improving by 39,

41, 60 and 72 % of the initial levels, respectively. Pain

intensity and bothersomeness improved markedly during

the first 6 months (35 and 37 %, respectively) with mini-

mal further reductions up to 12 months (39 and 41 %,

respectively). Conversely, disability and function contin-

ued to improve considerably throughout the 12 months.

After 3, 6 and 12 months, 19 (16 %), 30 (25.5 %) and

29 (25 %) participants had completely recovered (pain

score 0 or 1 for 1 month at time of assessment) from their

LBP, respectively.

The results of the univariate analysis are presented in

Table 3. Table 4 presents the results of the multivariate

backward regression analysis. Baseline pain intensity was

the only independent predictor of 12-month pain scores and

accounted for only 10 % (R2 = 0.102) of the outcome

variance (Table 4). Duration of current episode, disability

and educational level were independent predictors of dis-

ability accounting for 15 % of the variation on disability at

12 months (Table 4).

Discussion

Summary of main findings

The primary finding of this study is that patients with

chronic LBP who presented to a private, community-based,

group exercise program incorporating cognitive behavior

therapy improved substantially over the course of 1 year.

During the first 6 months disability, function and pain

intensity improved similarly; however between 6 and

12 months disability and function continued to improve

while only small further improvements in pain occurred. At

12 months pain intensity had reduced on average by 39 %

while disability and function had improved by 60 and

72 %, respectively.

The predictors investigated did not explain a substantial

amount of the variation in outcome for either pain or dis-

ability. The only independent predictor of 12-month pain

outcomes was baseline pain intensity, but this accounted

for only 10 % of the variation. The independent predictors

of 12-month disability were duration of current episode,

baseline disability and educational level, accounting for

15 % of the variation at 12 months.

Strengths and limitations of the study

A strength of this study is the inclusion of a clearly defined

cohort of consecutive patients with chronic LBP

([3 months) that enrolled in a private paying group exer-

cise program. The high 1-year follow-up rate (95 %) and

the use of validated outcome measures are further

strengths. Nevertheless, we understand that an even longer

follow-up period with more regular sampling may give a

more comprehensive assessment of the course of chronic

LBP.

We limited the number of baseline prognostic factors

investigated to one per ten patients, which could have ruled

out some important prognostic factors already investigated

by others studies, although inclusion of too many variables

Table 1 Baseline characteristics of study population

Characteristics No (%) or mean

(±SD)

Gender (female) 86 (73)

Age (years) 46.5 ± 12.5

Weight (kg) 72.5 ± 15.5

Height (cm) 171 ± 8.5

Smoker 5 (4)

Socioeconomic status (n = 118)

Resides in suburb with mean household income

above Australian mean

117 (99)

Previous episodes of LBP (n = 113)

Never 9 (7.5)

1–5 26 (22.5)

6–10 11 (9.5)

11 or over 71 (60.5)

Previous sick leave due to LBP (n = 116) 65 (55)

Previous treatment for LBP (n = 118) 114 (96.5)

Duration of current episode of LBPa, median

(IQR) (n = 113)

365 (172-730)

Leg painb (n = 112) 23 (19.5)

Highest level of education diploma or higherc

(n = 109)

97 (82)

Employment status before episode of LBP (n = 113)

Full time/full duties 82 (69.5)

Part time/full duties 14 (12)

Not seeking employment (retired/child care) 12 (10)

Work status changed as result of LBP (n = 113) 10 (8.5)

Current employment status (n = 113)

Full time/full duties 62 (52.5)

Full time/selected duties 6 (5)

Part time/full duties 19 (16)

Part time/selected duties 2 (1.7)

Not seeking employment (retired/child care) 24 (20)

Private health insurance 103 (87)

Pain catastrophizing scale (n = 112) 16 ± 10

IQR interquartile rangea Measured in daysb Defined as back pain extending below the kneec University study based

116 Eur Spine J (2014) 23:113–119

123

141

into the model makes it less stable and less generalizable

[18].

Comparison with existing literature

Our study found a more favorable prognosis for people

with chronic LBP than widely reported in the literature.

Van Tulder et al. [19] reported only small improvements in

pain intensity and disability after 12 months (14.2 and

14.7 %, respectively). Grotle and colleagues [5], found

only moderate changes in disability after 1 year (25 %

reduction) for people with chronic LBP. When comparing

the prognosis of our study participants to previous

literature, it is important to realize we aimed to recruit a

cohort lacking many of the previously reported adverse

prognostic factors and who were receiving recommended

care. As such we hypothesized that patients presenting with

a high educational and socioeconomic status and drawn

from a private paying, community-based, group exercise

program incorporating cognitive behavioral therapy, would

have a more favorable prognosis than widely reported for

chronic LBP. The results of the study support our

hypothesis. The prognosis found in this study may not

generalize well to patients in other settings where these

favorable prognostic factors are not present.

An interesting finding in our study was that disability

and function improved more than pain, especially between

6 and 12 months. These findings are consistent with results

from a previous trial [20] where patients receiving a pro-

gram based on cognitive behavioral principles, similar to

our cohort, improved by 49 % for disability but only 29 %

for pain after 12 months. Similar findings of greater

changes in disability than pain were also reported by a

systematic review of multidisciplinary rehabilitation for

chronic LBP [21]. Conversely a recent systematic review

of the prognosis of persistent LBP [2] found greater

changes in pain than disability over 12 months. The studies

included in this review did not typically include exercise

programs with cognitive behavioral principles and may

explain these differences in findings.

Our study found few important predictors of 12 month

pain or disability. Multivariate models predicted only 10

Table 2 Primary and secondary outcomes

Outcomes Baseline

mean ± SD

3 months

mean ± SD

3 months

percentage of

change

6 months

mean ± SD

6 months

percentage of

change

12 months

mean ± SD

12 months

absolute change

scoresg ± SD

12 months

percentage

of change

Bothersomenessa 5.4 ± 2.5 4.1 ± 2.2* 24 3.4 ± 2.3* 37 3.2 ± 2.4* 2.2 ± 3.2 41

Global

impression of

recoveryb

0.25 ± 2.4 1.5 ± 1.9* – 2.1 ± 1.7* – 2.5 ± 2* – –

Painc 4.4 ± 2.1 3.7 ± 2.1* 16 2.9 ± 2* 35 2.7 ± 2.2* 1.7 ± 2.6 39

Functiond 12.3 ± 5.3 15.5 ± 6.1* 26 18 ± 6* 46 21.1 ± 6* 8.8 ± 9.4 72

Disabilitye 7.8 ± 4.2 5.2 ± 4.2* 34 4.1 ± 4* 48 3.1 ± 3.2* 4.7 ± 4.5 60

Kinesiophobiaf 36 ± 7.5 34.8 ± 7.3 4 32.8 ± 7* 9 31 ± 7* 5 ± 10.7 14

* Significant mean difference between baseline data and 3, 6 or 12 months (p \ 0.05)a Rated on scale from 0 = not at all bothersome to 10 = extremely bothersomeb Rated on scale from -5 = vastly worse, 0 = unchanged to 5 = completely recoveredc Rated on scale from 0 = no pain to 10 = worst pain possibled Sum of the activities scores on a scale from 0 = unable to perform activity to 10 = able to perform activity at pre-injury level, divided by the

number of activitiese Rated from 0 to 24, with higher scores indicating a higher level of disabilityf A total score was calculated after inversion of the individual scores of items 4, 8, 12 and 16. Rated from 17 to 68, with higher scores indicating

a high degree of kinesiophobiag 12 months absolute scores are based on the difference between baseline scores and 12 months follow-up

Fig. 1 Percentage improvement in function, disability, pain intensity

and bothersomeness

Eur Spine J (2014) 23:113–119 117

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and 15 % of pain and disability outcomes, respectively.

These findings are somewhat lower than previous studies

although most previous studies have failed to identify

strong predictors of outcome in chronic LBP. Bekkering

et al. [22] followed a mixed group (acute/chronic LBP) of

500 patients with non-specific LBP for 12 months. This

study evaluated prognostic factors associated with pain and

disability at 12 months follow-up. The final model con-

sisted of two factors for pain (duration of the current epi-

sode and pain intensity at baseline) and three for disability

(paid job, episode duration and disability), these factors

explained 10 and 28 %, respectively, of the variance.

Grotle et al. [5], found five prognostic factors associated

with 12-month disability in people with chronic LBP

(being not employed widespread pain, chronic pain grade,

fear of pain and catastrophizing), representing 52.7 % of

variance. However, they note that beyond baseline

disability the effect size for most predictors is relatively

low. A possible reason predictors in our study failed to

explain much of the variance may be that we deliberately

included a cohort lacking most of the previously described

prognostic factors. In this population, predicting outcome

may be more difficult or other predictors may be more

important.

Conclusions

Over the course of 1 year, patients with chronic LBP who

presented to a private paying, community-based, group

exercise program incorporating cognitive behavioral ther-

apy, improved markedly. During the first 6 months, pain

intensity, bothersomeness, disability and function improved

similarly, but from 6 to 12 months, disability and function

Table 3 Univariate regression analysis with pain intensity and disability at 12 months follow-up as the dependent variable

Prognostic factors Pain intensity Disability

N R2 Unstandardized coefficient

(95 % CI)

p value R2 Unstandardized coefficient

(95 % CI)

p value

Number of previous episodesa 113 0.010 -0.650 (-1.889 to 0.589) 0.589 0.011 -0.016 (-2.798 to 0.766) 0.261

Pain intensityb 113 0.101 0.342 (0.150 to 0.534) 0.001 0.039 0.307 (0.021 to 0.592) 0.035

Duration of current episodec 113 0.006 0.148 (-0.211 to 0.508) 0.416 0.047 0.601 (0.094 to 1.108) 0.021

Disabilityd 113 0.013 0.061 (-0.039 to 0.160) 0.231 0.106 0.249 (0.113 to 0.386) \0.001

Functione 107 0.001 -0.013 (-0.095 to 0.069) 0.753 0.003 -0.035 (-0.154 to 0.083) 0.556

Global impression of recoveryf 113 0.054 -0.218 (-0.390 to -0.046) 0.014 0.007 -0.116 (-0.369 to 0.138) 0.369

Kinesiophobiag 113 0.034 0.055 (0.001 to 0.110) 0.049 0.040 0.085 (0.006 to 0.164) 0.034

Educational Levelh 109 0.006 0.485 (-0.743 to 1.714) 0.435 0.028 1.536 (-0.210 to 3.281) 0.084

Leg Paini 112 0.008 0.500 (-0.551 to 1.550) 0.348 0.006 0.617 (-0.894 to 2.128) 0.420

Catastrophizingj 112 0.044 0.047 (0.006 to 0.089) 0.027 0.031 0.057 (-0.003 to 0.118) 0.063

Patients enrolled for the 2nd termk 113 0.014 0.553 (-0.320 to 1.425) 0.212 0.001 -0.253 (-1.517 to 1.010) 0.692

11 point prognosis scalel 113 0.001 -0.040 (-0.278 to 0.198) 0.739 0.017 0.234 (-0.105 to 0.574) 0.174

a An episode of LBP was classified as pain lasting for more than 24 h. Scored as 0 (from 0 to 1 episode) or 1 (from two or more episodes)b Rated on a scale from 0 = no pain to 10 = worst pain possiblec Duration of the current episode was recorded in days and log transformed for the analysesd Rated from 0 to 24, with higher scores indicating a higher level of disabilitye Sum of the activities scores on a scale from 0 = unable to perform activity to 10 = able to perform activity at pre-injury level divided by the

number of activitiesf Rated on scale from -5 = vastly worse, 0 = unchanged to 5 = completely recoveredg A total score was calculated after inversion of the individual scores of items 4, 8, 12 and 16. Rated from 17 to 78, with higher scores indicating

a high degree of kinesiophobiah Educational level was score from 0 = school and technical college (school, high school certificate and trade) to 1 = University study based

(diploma, advanced diploma, bachelor degree and postgraduate degree)i Defined as back pain extended below the knee. Scored as 0 = no or 1 = yesj The Pain Catastrophizing Scale sum score was calculated from all items (range, 13–65), with a higher scores indicating a higher level of pain

catastrophizingk Patients who continues classes after the first term. Scored as 0 = patients enrolled for one term only or 1 = patients enrolled for two or more

termsl Rated from 0 to 10, with higher values indicating worse prognosis

118 Eur Spine J (2014) 23:113–119

123

143

continued to improve while only small further changes in

bothersomeness and pain intensity occurred.

Pain intensity at baseline was the only independent

predictor of 12-month pain scores, accounting for 10 % of

the variation. There were three independent predictors of

12 months disability; duration of current episode, baseline

disability and educational level, accounting for 15 % of the

variation. Most of the variance in outcome was not

explained by any of the predictors we investigated in this

study.

Acknowledgments We thank all staff at the Willoughby and Sta-

dium Physiocise clinics for their valuable assistance and support of

this study.

Conflict of interest None.

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pain: a meta-analysis. CMAJ 184(11):E613–E624

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back pain: a proposal for uniform definitions to be used in

research. Spine 27:2409–2416

5. Grotle M, Foster NE, Dunn KM, Croft P (2010) Are prognostic

indicators for poor outcome different for acute and chronic low

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7. Hayden JA, Chou R, Hogg-Johnson S, Bombardier C (2009)

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Table 4 Backward regression analyses with pain intensity (n = 112)

and disability (n = 108) at 12 months follow up as dependent

variable

Predictors R2 Regression coefficient

(95 % CI)

Pain intensity at 12 months

(n = 112)

0.102

Pain intensity at baselinea 0.344 (0.050 to 0.534)

Constant 1.244 (0.323 to 2.195)

Disability at 12 months

(n = 109)

0.154

Duration of current episodeb 0.457 (-0.048 to 0.961)

Disabilityc 0.234 (0.095 to 0.372)

Educational leveld 1.408 (-0.260 to 3.075)

Constant -2.505 (-5.825 to 0.815)

a Rated on a scale from 0 = no pain to 10 = worst pain possibleb Duration of the current episode was recorded in days and log

transformed for the analysesc Rated from 0 to 24, with higher scores indicating a higher level of

disabilityd Educational level was scored from 0 = school and technical col-

lege (school, high school certificate and trade) to 1 = University

study based (diploma, advanced diploma, bachelor degree and post-

graduate degree)

Eur Spine J (2014) 23:113–119 119

123

144

Chapter Eight

Do magnetic resonance imaging findings identify patients with low back pain who

respond better to particular interventions? A systematic review

Chapter Eight published as:

Steffens D, Hancock MJ, Pereira LSM, Kent PM, Latimer J, Maher CG. Do magnetic

resonance imaging findings identify patients with low back pain who respond better to

particular interventions? A systematic review. Submitted for publication to European

Journal of Pain on 28th

October 2014.

145


As co-authors of the paper “Do magnetic resonance imaging findings identify patients with

low back pain who respond better to particular interventions? A systematic review”, we

confirm that Daniel Steffens has made the following contributions:

Data extraction, analysis and interpretation of the findings




Peter M Kent Date: 01.01.2015



146

Title page

Title: Do magnetic resonance imaging findings identify patients with low back pain who

respond better to particular interventions? A systematic review.

Running head: MRI findings as effect modifiers for specific interventions.

Authors: D. Steffens1,3

, M.J. Hancock2, L.S.M. Pereira

3, P.M. Kent

4,5, J. Latimer

1, C.G.

Maher1

1 Musculoskeletal division, The George Institute for Global Health, Sydney Medical School,

The University of Sydney, Australia.

2 Discipline of Physiotherapy, Faculty of Human Sciences, Macquarie University, Sydney,

Australia.

3 Department of Physiotherapy, Federal University of Minas Gerais, Minas Gerais, Brazil.

4 Department of Sports Science and Clinical Biomechanics, University of Southern Denmark,

Odense, Denmark.

5 Research Department, The Spine Centre of Southern Denmark, Institute of Regional Health

Services Research, University of Southern Denmark, Middelfart, Denmark.

Correspondence: Daniel Steffens, The George Institute for Global Health, Sydney Medical

School, The University of Sydney, P.O. Box M201 Missenden Rd, Sydney, 2050, New South

Wales, Australia, phone 61 2 8238-24 34, fax 61 2 9657-0301, email address

[email protected]

Article category: Review article.

Funding sources: None declared.

Conflict of interest: None declared.

147

Databases:

This systematic review identified relevant studies by electronic searches of MEDLINE,

EMBASE, The Cochrane Central Register of Controlled Trials and by examination of

the reference lists of identified papers.

What does this review add?

The included studies investigated 38 interactions for combinations of different MRI

findings, interventions and outcomes.

Individual trials suggested some MRI findings might be effect modifiers for specific

interventions.

The limited number of suitable studies and the heterogeneity between them did not

permit definitive conclusions about effect modification.

Abstract

Background and Objective: Magnetic resonance imaging (MRI) can reveal a range of

degenerative findings and anatomical abnormalities; however, the clinical importance of

these remains uncertain and controversial. We aimed to investigate if the presence of MRI

findings identifies patients with LBP who respond better to particular interventions.

Databases and data treatment: MEDLINE, EMBASE and CENTRAL databases were

searched. We included RCTs investigating MRI findings as treatment effect modifiers for

patients with LBP or sciatica. We excluded studies with specific diseases as the cause of

LBP. Risk of bias was assessed using the criteria of the Cochrane Back Review Group.

Each MRI finding was examined for its individual capacity for effect modification.

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Results: Eight published trials met the inclusion criteria. The methodological quality of trials

was inconsistent. Substantial variability in MRI findings, treatments and outcomes across

the eight trials prevented pooling of data. Patients with Modic Changes type 1 when

compared with patients with Modic Changes type 2 had greater improvements in function

when treated by Diprospan (steroid) injection, compared with saline. Patients with central

disc herniation when compared with patients without disc herniation had greater

improvements in pain when treated by surgery, compared with rehabilitation.

Conclusions: Although individual trials suggested some MRI findings might be effect

modifiers for specific interventions, none of these interactions were investigated in more

than a single trial. High quality, adequately powered trials investigating MRI findings as

effect modifiers are essential to determine the clinical importance of MRI findings in LBP

and sciatica (PROSPERO: CRD42013006571).

Systematic Review Registration Number: PROSPERO: CRD42013006571.

1. Introduction

Low back pain (LBP) is an extremely common health problem (Hoy et al., 2010), with an

enormous global burden (Buchbinder et al., 2013). Limited progress has been made in the

management of LBP with most treatments showing little or no effect (Keller et al., 2007; van

Tulder et al., 2006). One explanation for this lack of progress might be the current inability to

identify a specific cause for LBP in most people (van Tulder et al., 2006). As a result, a single

intervention is usually provided to heterogeneous groups of patients with potentially different

causes of their pain. Identifying more homogenous subgroups of LBP patients has been

identified as a key research priority in the field (Costa Lda et al., 2013). Most previous

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research in this area has focussed on identifying clinical and psychosocial variables

associated with patients who respond better to different interventions (Kent and Kjaer, 2012;

Kent et al., 2010b). However, very little attention has focussed on identifying subgroups

based on biological mechanisms or anatomical structures. Some early work has investigated

subgroups based on different pain mechanisms (Smart et al., 2012; Rabey et al., 2014; Vibe

Fersum et al., 2013) due to increasing evidence for the role of central mechanisms in the

development of chronic LBP (O’Sullivan 2005). Subgrouping based on possible peripheral

patho-anatomical causes of LBP has received little attention and its value is unknown.

The importance of magnetic resonance imaging (MRI) findings such as disc herniation, facet

joint arthropathy and modic changes (bone marrow and endplate lesions visible on MRI) in

identifying the source of an individual patient’s LBP remains unclear and controversial.

Many MRI findings are common in people without LBP, yet these findings are typically

more common in people with LBP than those without (Cheung et al., 2009; Hancock et al.,

2012; Steffens et al., 2013). Research into the importance or otherwise of MRI findings has

been frustrated by the lack of a widely accepted gold standard (Hancock et al., 2012). An

alternative approach in such cases is to investigate if the presence of MRI findings predicts

different response to interventions (Rutjes et al., 2007). If this were the case, it would provide

evidence for the importance of such findings and a logical rationale for selecting specific

interventions for individual patients.

To our knowledge, there has been no review of diverse MRI findings as effect modifiers for

LBP interventions. Therefore, the aim of this systematic review was to investigate if the

presence of MRI findings at baseline identifies patients with LBP who respond better to

particular interventions.

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2. Methods

The review protocol was specified in advance and registered on PROSPERO: International

prospective register of systematic reviews (refer to this link for full access of the protocol,

http://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD42013006571). The

PRISMA statement was used to guide the conduct and reporting of the study (Moher et al.,

2009).

2.1 Search strategy

A sensitive search was performed of MEDLINE, EMBASE and The Cochrane Central

Register of Controlled Trials to identify potential studies from the earliest records up to 1st of

December, 2013. We used a search strategy based on the recommendations of the Cochrane

Back Review Group (Furlan et al., 2009) for randomised controlled trials (RCTs) and LBP,

combined with Medical Subject Headings and keywords related to ‘MRI’ and ‘effect

modification/ subgroups’. After piloting the search strategy we decided to use two different

searches and then combine the results.

Search 1 included terms from each of the following domains (i) RCTs, (ii) LBP and (iii)

MRI. Search 2 included terms from each of the following domains (i) RCTs, (ii) LBP and

(iii) effect modification/ subgroup. Searches 1 and 2 were merged to generate the final search

strategy (Refer to Appendix S1 and S2 for the full search strategy). Reference and citation

tracking of relevant articles were performed. A final list of the included studies was sent to

two experts in the field who reviewed the list for possible omissions.

2.2 Study selection

To be included, studies were required to meet all of the following criteria:

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(i) Participants: Recruited samples of populations with current LBP or sciatica, who were not

diagnosed with serious disease (e.g. cancer, spinal infection, spinal fracture, inflammatory

arthritis or cauda equina syndrome) as the source of LBP.

(ii) Interventions: Investigated any type of intervention for LBP, including conservative,

surgical, or placebo. Included studies needed to have compared any intervention for LBP or

sciatica, with any type of intervention, placebo or no treatment control.

(iii) Outcome: Reported for either pain (e.g. measured by the Visual Analogue Scale,

Numerical Rating Scale) or disability (e.g. measured by the Roland Morris Disability Scale,

Oswestry Disability Scale). In studies that included participants with a primary complaint of

LBP, self-reported LBP was considered the primary outcome while in trials of sciatica self-

reported leg pain was considered the primary outcome.

(iv) Study design: Included studies needed to be an RCT which had used methods capable of

identifying whether patients with a specific MRI finding had a different treatment effect than

those without the MRI finding or with a different MRI finding. Studies were required to have

included and reported a patient’s results separately for either (a) sample with and without a

particular MRI finding (i.e. disc herniation) or (b) people with a different type or severity of

MRI finding (i.e. mild vs. severe disc degeneration).

One reviewer screened titles and abstracts of each citation and excluded clearly irrelevant

studies. For each potentially eligible study the full text was retrieved and two reviewers

independently assessed whether the study fulfilled the inclusion criteria. In cases of

disagreement, a third reviewer was consulted and a decision made by consensus. The search

had no language restrictions.

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2.3 Data extraction

Relevant data were independently extracted by two reviewers using a standardised form. In

cases of disagreement, a joint review of the original article was performed until consensus

was reached. The extraction form included the following criteria: clinical settings, sample,

age, treatment groups, MRI findings and point estimates and measures of variability for

outcomes. Outcome data were extracted for short-term outcomes (0 to ≤ 6 months) and long-

term outcomes (>6 months). When multiple time points fell within the same category, we

used the one closest to 3 months for short-term and closest to 12 months for long-term.

2.4 Risk of bias

Risk of bias was assessed using criteria recommended by the Cochrane Back Review Group

(Furlan et al., 2009). Two reviewers independently assessed the criteria of all included

studies. In cases of disagreement, a third reviewer was consulted and a decision made by

consensus (refer to Appendix S3 for further details on the criteria list for the methodological

quality assessment). Data pooling was appropriate only if the studies were considered

homogeneous with regard to population sample, MRI measure, clinical outcomes and

treatment.

2.5 Analysis

It eventuated that we were unable to undertake the pre-specified meta-analysis due to the

small number of included trials and the heterogeneity between them in terms of MRI

findings, treatment and clinical outcomes. Therefore, each MRI finding of the lumbar spine

was examined for its individual capacity for effect modification and interaction. The results

are presented descriptively for LBP and sciatica populations.

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We extracted (i) mean difference and 95% confidence intervals (95% CI) from studies that

reported continuous outcomes, (ii) hazard ratios (HR) and 95% CI from studies that reported

time-to-event categorical outcomes, and (iii) contingency table data to calculate Odds Ratios

(OR) for categorical outcomes. If not reported or provided, the effect modification and

subgroup interaction was calculated using the method suggested by Kent et al (Kent et al.,

2010b) for continuous outcomes and the method suggested by Hancock et al (Hancock et al.,

2013) for categorical outcomes.

Four studies had key information not available from published manuscripts and additional

information was requested (Arts et al., 2010; Pearson et al., 2012; Pearson et al., 2008; Peul

et al., 2009). Two studies reported combined RCT and observational cohort data (Pearson et

al., 2012; Pearson et al., 2008). The separated RCT data for the intention-to-treat analysis was

requested. The effect modification and/or the subgroup interaction were calculated by the

current review authors, for six studies (Buttermann, 2004; Cao et al., 2011; Hellum et al.,

2012; Pearson et al., 2012; Pearson et al., 2008; Tafazal et al., 2009).

In this review, the term subgroup interaction refers to how much more effective (compared

with the control intervention) the intervention is in the subgroup (MRI positive) than for

those not in the subgroup (MRI negative).

3. Results

3.1 Study Selection

The search identified 6239 papers. After review of titles and abstracts, we excluded 6186

(Figure 1). Based on full-text review of 53 papers, we excluded a further 45 and included

eight trials in the review (Arts et al., 2010; Buttermann, 2004; Cao et al., 2011; Hellum et al.,

2012; Pearson et al., 2012; Pearson et al., 2008; Peul et al., 2009; Tafazal et al., 2009). The

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primary reasons for the exclusion of trials retrieved in full-text are noted in Appendix S4. No

additional studies were identified after contacting two experts in the field of MRI and LBP.

3.2 Risk of bias

The risk of bias assessments for the included studies are shown in Table 1. Randomisation,

drop-out rate, co-interventions and outcome timing were the only criteria scored ‘yes’ in all

trials. Participant blinding, outcome assessor blinding and absence of selective outcome

reporting were the criteria most commonly scored ‘no’.

3.3 Study Characteristics

The characteristics of the included studies are shown in Table 2. Three trials studied patients

with LBP (Buttermann, 2004; Cao et al., 2011; Hellum et al., 2012) and five studied patients

with sciatica (Arts et al., 2010; Pearson et al., 2012; Pearson et al., 2008; Peul et al., 2009;

Tafazal et al., 2009). The samples were recruited from secondary health care (Arts et al.,

2010; Buttermann, 2004; Pearson et al., 2012; Pearson et al., 2008; Tafazal et al., 2009), and

tertiary health care (Cao et al., 2011; Hellum et al., 2012; Peul et al., 2009) settings. The

number of participants varied from 120 to 472 and most studies sampled predominantly

adults in their middle age. The treatments evaluated in the trials included surgery, injections

and rehabilitation. No study had the primary aim of investigating MRI effect modifiers. LBP

duration was categorised as acute (less than 6 weeks), sub-acute (6-12 weeks) and chronic

(greater than 12 weeks) (Furlan et al., 2009).

3.4 Results of the review

Due to the heterogeneity of samples, MRI findings, clinical outcomes and treatment, it was

not possible to perform meta-analysis of the results for any of the included studies. For ease

of interpretation, the studies were grouped into LBP population (Buttermann, 2004; Cao et

155

al., 2011; Hellum et al., 2012) or sciatica population (Arts et al., 2010; Pearson et al., 2012;

Pearson et al., 2008; Peul et al., 2009; Tafazal et al., 2009) as the importance of MRI findings

might be quite different in these two populations. Detailed findings of all included studies are

presented in Table 3.

3.4.1 Low back pain population samples

One study reported on a population with sub-acute LBP (symptoms ≥ 6 weeks) (Cao et al.,

2011) and two reported on populations with chronic LBP (symptoms ≥ 1 year) (Buttermann,

2004; Hellum et al., 2012). All three studies investigated Modic changes (Modic changes type

1 corresponding to vertebral body edema and hyper-vascularity; Modic changes type 2

reflecting fatty replacements of the red bone marrow; and Modic changes type 3 consisting of

subchondral bone sclerosis (Modic et al., 1988a; Modic et al., 1988b)) as effect modifiers

(Buttermann, 2004; Cao et al., 2011; Hellum et al., 2012), while one study investigated disc

herniation and facet joint arthritis (Hellum et al., 2012).

Cao et al (Cao et al., 2011) investigated various intradiscal injection regimens for patients

with Modic changes (n=120). Patients with Modic changes type 1, when compared with

patients with Modic changes type 2, had greater improvements in disability in the short-term

(3 months) when treated by Diprospan (steroid) injection, compared with saline (mean

difference 8.30; 95% CI, 1.01 to 15.59, on a 0 to 100 disability scale). Other subgroup

interactions for pain and disability with Modic changes were not significant.

Hellum et al (Hellum et al., 2012) investigated whether features of degenerative disc were

effect modifiers for disc prosthesis compared with multidisciplinary rehabilitation at two-year

follow up (n=154). The presence of Modic changes type 1 and/or 2 was not a significant

effect modifier for improvements in disability (percentage of patients improved ≥15 points on

a 0 to 100 scale, categorized by yes/no), OR ranging from 0.63 (95% CI, 0.15 to 2.65) to 2.96

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(95% CI, 0.65 to 13.52). Similarly, disc herniation, facet joint arthropathy and high intensity

zone were not significant effect modifiers for improvement in disability when treated with

surgery, compared with rehabilitation (Hellum et al., 2012).

Buttermann (Buttermann, 2004) investigated whether Modic changes type 1 was an effect

modifier for spinal injection and steroid, compared with discography alone at 1-3 and 12-24

months (n=171). Presence of Modic changes type 1 was not a significant effect modifier for

injection success (coded as ‘yes’ if the overall opinion about their injection was considered

successful) at short (OR, 7.94; 95% CI, 0.40 to 156.46) or long-term follow up (OR, 2.20;

95% CI, 0.11 to 45.98).

3.4.2 Sciatica population samples

Three studies reported potential MRI effect modifiers in one population sample with sub-

acute sciatica (symptoms ≥6 weeks) (Arts et al., 2010; Peul et al., 2009; Tafazal et al., 2009)

and two with chronic sciatica (symptom ≥12 weeks) (Pearson et al., 2012; Pearson et al.,

2008). Three studies investigated disc herniation (Arts et al., 2010; Pearson et al., 2008; Peul

et al., 2009), two investigated spinal stenosis (Arts et al., 2010; Pearson et al., 2012), one

investigated disc height (Arts et al., 2010) and one investigated different types of MRI

findings (disc prolapse vs. spinal stenosis) (Tafazal et al., 2009) as effect modifiers.

Pearson et al (Pearson et al., 2008) studied whether features of disc herniation were effect

modifiers for discectomy, compared with conservative rehabilitation at three and 12 months

follow up (n=472). Patients with central disc herniation, when compared with patients

without central disc herniation, had better response to surgery at long-term follow up (24

months), mean difference 1.60; 95% CI, 0.17 to 3.03 (0 to 6 point Likert scale). In patients

with central herniation, one-year pain outcomes were better (mean difference 1.60; 95% CI,

0.10 to 3.10; 0 to 6 point Likert scale) for those receiving surgery compared with

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rehabilitation. In those without central herniation, surgery was no better than rehabilitation

(mean difference 0.00; 95% CI, -0.40 to 0.40; 0 to 6 point Likert scale). Other disc herniation

characteristics (e.g. posterolateral and protrusion) were not associated with significant

treatment interactions.

Peul et al (Peul et al., 2009) investigated if disc herniation was an effect modifier for

response to early surgery compared with prolonged conservative care (n=283). Sequestrated

disc herniation (Hazard ratio, 0.94; 95% CI, 0.56 to 1.57) and disc herniation enhancement

(Hazard ratio, 0.85; 95% CI, 0.47 to 1.54) did not have any significant interaction with

treatment at 12 months (very much improved and much improved were coded as recovered).

Arts et al (Arts et al., 2010) investigated if disc herniation, spinal stenosis and disc height

were effect modifiers for response to tubular discectomy, compared with conventional

microdiscectomy, at one-year follow up (n=325). None of the MRI findings produced

significant interactions with treatment for long-term recovery outcomes.

Pearson et al (Pearson et al., 2012) investigated whether features of spinal stenosis were

effect modifiers for response to surgery, compared with rehabilitation, in 278 patients at three

and 24 months follow up. Spinal stenosis did not produce any significant interactions with

treatment for short- and long-term disability outcomes.

Tafazal et al (Tafazal et al., 2009) investigated whether features of disc herniation (disc

prolapse) or lumbar spinal stenosis were effect modifiers for the efficacy of corticosteroids

injection in 150 patients. Neither MRI features produced significant interactions with

bupivacaine (a local anaesthetic) and steroid or bupivacaine alone at short-term follow up.

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4. Discussion

4.1 Statement of principal findings

This review could only identify eight studies, which provided adequate data to assess if MRI

findings were treatment effect modifiers. The included studies investigated 38 interactions for

combinations of different MRI findings, interventions and outcomes. No effect modifiers

were consistently identified across more than one study. Individual trials suggested some

MRI findings might be effect modifiers for specific interventions. However, these are single

study results and caution should be taken when interpreting the findings. Some other

subgroup interactions presented trends and confidence intervals that included potentially

important interactions; however, these trials were underpowered due to their small sample

sizes.

4.2 Strengths and weaknesses of the study

We believe this is the first systematic review of RCTs to investigate if diverse MRI findings

are effect modifiers for interventions in people with LBP and/or sciatica. The strength of this

review is the use of a pre-specified protocol and the comprehensive approach to identifying

all suitable RCTs. We also provide data for all included trials on the interaction effect as well

as the subgroup effects for those with and without the MRI finding of interest. We used a

sensitive search strategy and contacted experts in the field, reducing the risk of missing any

important trial. Despite this, we could have missed important studies because of human error

or because they were contained in databases that were not searched. A limitation of our

review is that the inconsistency of MRI findings, interventions and outcomes investigated

across the studies, inhibited our ability to perform meta-analysis. Furthermore, most trials

were not powered for subgroup interaction analysis, as it was not the primary aim of the

study. As a result, some non-significant findings may include a potentially important

159

interaction (e.g. OR, 7.94; 95% CI, 0.40 to 156.46) (Buttermann, 2004). Another limitation of

our review is the possibility of publication bias as, beyond contacting two content experts, we

did not attempt to identify unpublished trials that might have been found in other clinical

trials registries and in conference proceedings.

4.3 Comparison with other studies

Three previous reviews have investigated effect modifiers for LBP treatments. Two of these

reviews investigated effect modifiers for specific interventions (manual therapy/exercise and

psychosocial intervention) (Kent and Kjaer, 2012; Kent et al., 2010b). These reviews did not

include MRI findings as potential effect modifiers. One review specifically investigated

Modic changes as effect modifiers (Jensen and Leboeuf-Yde, 2011). Interestingly, all reviews

found a limited number of suitable studies, which had inconsistent findings, had small sample

sizes, and provided limited evidence for strong effect modifiers. These results corroborate our

findings. The review investigating Modic changes as an effect modifier for different LBP

treatments had several method limitations (Jensen and Leboeuf-Yde, 2011); for example, the

inclusion of single subgroup designs ( i.e. studies including all people with Modic changes

and no people without Modic changes) as these types of studies cannot robustly test if effect

modification occurred (Kent et al., 2010a).

4.4 Meaning of the study

From 38 subgroup interactions investigated, one presented a significant effect modifier for

LBP and one for sciatica populations. These positive findings could represent spurious

findings. However, the lack of statistically significant interactions may also be partly due to

most studies being underpowered for this type of analysis. Consequently, it remains unclear

whether MRI findings are important effect modifiers for interventions for LBP and sciatica

populations. What is clear is that there are very few trials and most of these are

160

underpowered, reinforcing the need for more and larger trials in this potentially important and

evolving area.

4.5 Recommendations for future research

Studies on subgroup interaction are a research priority in LBP (Costa Lda et al., 2013) and

well conducted trials provide the possibility to answer the important and controversial

question about the importance or otherwise of MRI findings. The need for larger, high-

quality trials is evident. Due to the nature of subgroup and interaction analyses, such trials

need a larger sample size than if their only interest was the main effect of treatment. Perhaps

one way to gain statistical power would be to combine several sets of individual patient data,

to acquire an adequate number of individuals with and/or without an MRI finding of interest.

Furthermore, future trials should adopt comprehensive and standardised methods for

measuring pain (i.e. pain rating scale).

A key finding from our review was that only trials including surgery or injections had

investigated MRI findings as effect modifiers for LBP interventions. We could find no

evidence for the importance or otherwise of MRI findings for conservative interventions.

While we recommend the need for larger, high-quality trials, it is important to note that

limited evidence exists for the use of surgery in most patients with LBP (Chou et al., 2009).

Therefore future trials investigating the importance of pathoanatomic findings in improving

outcomes from surgery should be limited to patient groups with indications for surgery, such

as those with sciatica or degenerative spondylolisthesis. The role of central pain processing is

known to be important in many people with chronic LBP (O’Sullivan 2005) and where this

predominates rather than peripheral nociceptive mechanisms it is unlikely that surgical

interventions will be effective regardless of pathoanatomic changes identified on MRI.

161

5. Conclusions

This review identified eight studies that investigated if MRI findings identify patients with

LBP and/ or sciatica who respond better to a variety of interventions. While two statistically

significant interactions were found between specific MRI findings and response to treatment,

the limited number of suitable studies and the heterogeneity between them did not permit

definitive conclusions about effect modification. Further well-designed, adequately powered

studies are required.

Acknowledgements

We thank Professor Michele Crites-Battie and Professor Jeffrey G. Jarvik for reviewing

included studies and suggesting possible additional studies. We also thank authors from the

included studies for providing additional information.

Author’s contributions

D.S., M.J.H. and C.G.M. contributed to the conception and design. All authors participated in

data acquisition, analysis and interpretation. D.S. drafted the article and all authors revised it

critically and gave the final approval of the version to be published.

162

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166

Figure and Tables’ legends

Figure 1. Flow chart diagram of review process.

Table 1. Assessment of risk of bias of the included studies.

Table 2. Individual characteristics of the included studies.

Table 3. Subgroup treatment effect and interaction for low back pain and sciatica population.

Appendix S1. Search strategy 1 (MEDLINE, EMBASE AND CENTRAL).

Appendix S2. Search strategy 2 (MEDLINE, EMBASE AND CENTRAL).

Appendix S3. Criteria list for the risk of bias assessment.

Appendix S4. List of excluded full-text articles and the primary reason for exclusion.

167

Records identified through database searching

MEDLINE = 2118 EMBASE = 5228

Cochrane Central = 438

Full-text articles assessed for eligibility (n=53)

RCTs included in review (n=8)

Full-text articles excluded

- Not an RCT (n=10) - No evaluation of MRI

findings (n=9) - Not possible to

elucidate association between MRI and outcome (n=26)

Ide

nti

fica

tio

n

Scre

en

ing

Incl

ud

ed

Additional records identified

through other sources (n=1)

Figure 1. Flow diagram of review process

Records excluded (n=6186)

Elig

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ty

Records after duplicates removed (n=6239)

168

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0 p

atie

nts

wit

h

sub

-acu

te s

ciat

ica

(≥6

wee

ks)

.

51

.90 (

?)

- P

ain (

VA

S,

ran

ges

fro

m 0

to

10

0,

wit

h 0

co

rres

po

nd

ing t

o n

o p

ain);

- D

isab

ilit

y (

OD

I, r

anges

fro

m 0

% t

o

10

0%

, w

ith 0

% c

orr

esp

ond

ing

to

no

dis

abil

ity).

1)

Inje

ctio

n:

2m

L o

f 0

.25

% b

up

ivac

aine

and

40

mg o

f m

eth

ylp

red

nis

olo

ne

(Dep

om

edro

ne)

;

2)

Inje

ctio

n:

2m

L o

f 0

.25

% b

up

ivac

aine

alo

ne.

3 m

onth

s

(82

.66

%)

?=

dat

a no

t av

aila

ble

; V

AS

=V

isual

anal

og

ue

scal

e;

OD

I=O

swest

ry d

isab

ilit

y i

nd

ex;

a Per

centa

ge

bas

ed o

n t

he

sam

ple

avai

lab

le f

or

the

sub

gro

up

inte

ract

ion.

171

Ta

ble

3.

Sub

gro

up

tre

atm

ent

effe

ct

and

in

tera

ctio

n f

or

low

bac

k p

ain a

nd

sci

atic

a p

op

ula

tio

n

MR

I fe

atu

re

MR

I th

resh

old

Stu

dy

Tre

atm

en

t

Tre

atm

en

t ef

fect

for

MR

I +

Tre

atm

en

t ef

fect

for

MR

I -

Cli

nic

al

ou

tco

me

(tim

e),

thre

sho

ld

Su

bg

rou

p

Inte

ract

ion

, m

ean

dif

feren

ce (

95

%

CI)

, u

nle

ss

oth

erw

ise

ind

ica

ted

Po

siti

ve

(+)

Neg

ati

ve

(-)

Tre

atm

en

t 1

T

rea

tmen

t 2

Lo

w b

ack

pa

in p

op

ula

tio

ns

Mo

dic

typ

e

Typ

e 1

T

yp

e 2

C

ao e

t al

. 2

01

1

Dip

rosp

an

Sal

ine

5.2

0 (

4.4

4 t

o 5

.96)

5.2

0 (

4.6

0 t

o 5

.80)

Pai

n (

ST

), 0

to

10

0.0

0 (

-0.9

8 t

o 0

.98

)

Mo

dic

typ

e

Typ

e 1

T

yp

e 2

C

ao e

t al

. 2

01

1

Dip

rosp

an +

song

mei

le

Sal

ine

5.0

0 (

4.2

9 t

o 5

.71)

5.2

0 (

4.6

0 t

o 5

.80)

Pai

n (

ST

), 0

to

10

-0.2

0 (

-0.7

4 t

o 1

.14

)

Mo

dic

typ

e

Typ

e 1

T

yp

e 2

C

ao e

t al

. 2

01

1

Dip

rosp

an+

song

mei

le

Dip

rosp

an

0.2

0 (

-0.4

0 t

o 0

.80

) 0

.00

(-0

.54

to

0.5

4)

Pai

n (

ST

), 0

to

10

0.2

0 (

-0.6

2 t

o 1

.02

)

Mo

dic

typ

e

Typ

e 1

T

yp

e 2

C

ao e

t al

. 2

01

1

Dip

rosp

an

Sal

ine

28

.90 (

22

.52 t

o

35

.28)

20

.60 (

15

.69 t

o

25

.51)

Dis

abil

ity

(ST

), 0

to

10

0

8.3

0 (

1.0

1 t

o 1

5.5

9)a

Mo

dic

typ

e

Typ

e 1

T

yp

e 2

C

ao e

t al

. 2

01

1

Dip

rosp

an +

song

mei

le

Sal

ine

28

.40 (

21

.95 t

o

34

.85)

20

.20 (

15

.17 t

o

25

.23)

Dis

abil

ity

(ST

), 0

to

10

0

8.2

0 (

-0.1

1 t

o 1

6.5

1)

Mo

dic

typ

e

Typ

e 1

T

yp

e 2

C

ao e

t al

. 2

01

1

Dip

rosp

an +

song

mei

le

Dip

rosp

an

0.5

0 (

-1.2

1 t

o 2

.21

) 0

.40

(-1

.35

to

2.1

5)

Dis

abil

ity

(ST

), 0

to

10

0

0.1

0 (

-2.3

9 t

o 2

.59

)

Mo

dic

typ

e 1

P

rese

nt

Ab

sent

Hel

lum

et

al.

20

12

Surg

ery

R

ehab

ilit

atio

n

6.0

7 (

1.6

6 t

o 2

2.1

2)b

2

.05

(0

.92

to

4.5

5)b

D

isab

ilit

y

(LT

), 0

to

10

0,

≥1

5po

ints

2.9

6 (

0.6

5 t

o 1

3.5

2)b

Mo

dic

typ

e 1

and

2

Pre

sent

A

bse

nt

Hel

lum

et

al.

20

12

Surg

ery

R

ehab

ilit

atio

n

3.2

1 (

0.6

6 t

o 1

5.5

9)b

2

.94

(1

.40

to

6.1

6)b

D

isab

ilit

y

(LT

), O

DI

0 t

o

10

0, ≥

15p

oin

ts

1.1

0 (

0.1

9 t

o 6

.27)b

Mo

dic

typ

e 2

P

rese

nt

A

bse

nt

Hel

lum

et

al.

20

12

Surg

ery

R

ehab

ilit

atio

n

2.1

6 (

0.6

7 t

o 6

.93)b

3

.43

(1

.48

to

7.9

3)b

D

isab

ilit

y

(LT

), 0

to

10

0,

≥1

5po

ints

0.6

3 (

0.1

5 t

o 2

.65)b

Mo

dic

typ

e 1

P

rese

nt

Ab

sent

Butt

erm

ann

20

04

Dis

cogra

ph

y +

ster

oid

D

isco

gra

ph

y

76

.85 (

9.4

7 t

o

62

3.5

2)b

9

.68

(1

.15

to

80

.91

)b

Succ

ess

(ST

),

yes

7

.94

(0

.40

to

15

6.4

6)b

Mo

dic

typ

e 1

P

rese

nt

Ab

sent

Butt

erm

ann

20

04

Dis

cogra

ph

y +

ster

oid

D

isco

gra

ph

y

12

.33 (

1.4

9 t

o

10

1.8

6)b

5

.61

(0

.63

to

50

.02

)b

Succ

ess

(LT

),

yes

2

.20

(0

.11

to

45

.98

)b

Dis

c

her

nia

tio

n

Hei

ght

red

uct

ion

No

hei

ght

red

uct

ion

Hel

lum

et

al.

20

12

Surg

ery

R

ehab

ilit

atio

n

2.6

1 (

1.1

7 t

o 5

.82)b

3

.64

(1

.04

to

12

.78

)b

Dis

abil

ity

(LT

), 0

to

10

0,

≥1

5po

ints

0.7

2 (

0.1

6 t

o 3

.18)b

Dis

c

her

nia

tio

n

Sig

nal

inte

nsi

ty

No

sig

nal

inte

nsi

ty

Hel

lum

et

al.

20

12

Surg

ery

R

ehab

ilit

atio

n

2.5

1 (

1.2

3 t

o 5

.13)b

1

2.0

0 (

1.0

5 t

o

13

6.7

9)b

Dis

abil

ity

(LT

), 0

to

10

0,

≥1

5po

ints

0.2

1 (

0.0

2 t

o 2

.64)b

172

Fac

et j

oin

t

arth

rop

aty

≥m

od

erat

e <

mo

der

ate

Hel

lum

et

al.

20

12

Surg

ery

R

ehab

ilit

atio

n

0.7

8 (

0.0

6 t

o 1

0.8

6)b

3

.15

(1

.55

to

6.3

8)b

D

isab

ilit

y

(LT

), 0

to

10

0,

≥1

5po

ints

0.2

5 (

0.2

0 t

o 3

.79)b

Hig

h i

nte

nsi

ty

zone

Pre

sent

Ab

sent

Hel

lum

et

al.

20

12

Surg

ery

R

ehab

ilit

atio

n

3.3

5 (

1.1

6 t

o 9

.72)b

2

.83

(1

.16

to

6.9

3)b

D

isab

ilit

y

(LT

), 0

to

10

0,

≥1

5po

ints

1.1

8 (

0.2

9 t

o 4

.75)b

Sci

ati

ca p

op

ula

tio

ns

Dis

c

her

nia

tio

n

Cen

tral

N

o C

entr

al

Pea

rso

n e

t al

.

20

08

Surg

ery

R

ehab

ilit

atio

n

1.8

0 (

0.3

0 t

o 3

.30)

0.1

0 (

-0.4

0 t

o 0

.60

) P

ain (

ST

), 0

to

6

1.7

0 (

-0.0

7 t

o 3

.47

)

Dis

c

her

nia

tio

n

Cen

tral

N

o C

entr

al

Pea

rso

n e

t al

.

20

08

Surg

ery

R

ehab

ilit

atio

n

1.6

0 (

0.1

0 t

o 3

.10)

0.0

0 (

-0.4

0 t

o 0

.40

) P

ain (

LT

), 0

to

6

1.6

0 (

0.1

7 t

o 3

.03)a

Dis

c

her

nia

tio

n

Po

ster

ola

tera

l N

o

po

ster

ola

tera

l

Pea

rso

n e

t al

.

20

08

Surg

ery

R

ehab

ilit

atio

n

0.2

0 (

-0.3

0 t

o 0

.70

) 0

.50

(-0

.50

to

1.5

0)

Pai

n (

ST

), 0

to

6

-0.3

0 (

-1.4

5 t

o 0

.85

)

Dis

c

her

nia

tio

n

Po

ster

ola

tera

l N

o

po

ster

ola

tera

l

Pea

rso

n e

t al

.

20

08

Surg

ery

R

ehab

ilit

atio

n

0.0

0 (

-0.5

0 t

o 0

.50

) 0

.60

(-0

.40

to

1.6

0)

Pai

n (

LT

), 0

to

6

-0.6

0 (

-1.7

8 t

o 0

.58

)

Dis

c

her

nia

tio

n

Pro

trusi

on

N

o p

rotr

usi

on

P

ears

on e

t al

.

20

08

Surg

ery

R

ehab

ilit

atio

n

0.6

0 (

-02

0 t

o 1

.40)

0.1

0 (

-0.4

0 t

o 0

.60

) P

ain (

ST

), 0

to

6

0.5

0 (

-0.4

5 t

o 1

.45

)

Dis

c

her

nia

tio

n

Pro

trusi

on

N

o p

rotr

usi

on

P

ears

on e

t al

.

20

08

Surg

ery

R

ehab

ilit

atio

n

0.3

0 (

-0.5

0 t

o 1

.10

) 0

.10

(-0

.40

to

0.6

0)

Pai

n (

LT

), 0

to

6

0.2

0 (

-0.7

6 t

o 1

.16

)

Dis

c

her

nia

tio

n

Seq

ues

trat

ed

Co

nta

ined

P

eul

et a

l. 2

009

S

urg

ery

R

ehab

ilit

atio

n

1.8

4 (

1.2

3 t

o 2

.75)c

1.9

6 (

1.4

0 t

o 2

.74)c

Rec

over

y

(LT

), ≥

much

imp

roved

0.9

4 (

0.5

6 t

o 1

.57)c

Dis

c

her

nia

tio

n

Seq

ues

trat

ed

Co

nta

ined

A

rts

et a

l. 2

01

0

Tub

ula

r

dis

cect

om

y

Co

nven

tio

nal

mic

rod

isce

cto

my

1

.10

(0

.82

to

1.4

6)c

0.7

3 (

0.4

9 t

o 1

.09)c

Rec

over

y

(LT

), ≥

alm

ost

com

ple

te

reco

ver

y

0.6

6 (

0.4

1 t

o 1

.09)c

Dis

c

her

nia

tio

n

Enhance

men

t N

o

enhance

men

t P

eul

et a

l. 2

009

S

urg

ery

R

ehab

ilit

atio

n

2.3

2 (

1.4

3 t

o 3

.77)c

1.9

7 (

1.3

8 t

o 2

.83)c

Rec

over

y

(LT

), ≥

much

imp

roved

0.8

5 (

0.4

7 t

o 1

.54)c

Dis

c

her

nia

tio

n

>1

/3 o

f sp

inal

canal

≤1

/3 o

f sp

inal

canal

A

rts

et a

l. 2

01

0

Tub

ula

r

dis

cect

om

y

Co

nven

tio

nal

mic

rod

isce

cto

my

0

.93

(0

.70

to

1.2

4)c

1.0

0 (

0.6

6 t

o 1

.49)c

Rec

over

y

(LT

), ≥

alm

ost

com

ple

te

reco

ver

y

0.9

4 (

0.5

7 t

o 1

.53)c

Dis

c

her

nia

tio

n

Med

iola

tera

l

and

lat

eral

M

edia

n

Art

s et

al.

20

10

T

ub

ula

r

dis

cect

om

y

Co

nven

tio

nal

mic

rod

isce

cto

my

0

.91

(0

.67

to

1.2

4)c

0.9

8 (

0.6

8 t

o 1

.40)c

Rec

over

y

(LT

), ≥

alm

ost

com

ple

te

reco

ver

y

1.0

7 (

0.6

7 t

o 1

.72)c

Sp

inal

C

entr

al

No

cen

tral

P

ears

on e

t al

. S

urg

ery

R

ehab

ilit

atio

n

0.6

0 (

-5.4

0 t

o 6

.60

) -1

1.0

0 (

-25

.70

to

D

isab

ilit

y

11

.60 (

-4.7

9 t

o 2

7.9

9)

173

sten

osi

s 2

00

12

3.7

0)

(ST

), 0

to

10

0

Sp

inal

sten

osi

s C

entr

al

No

cen

tral

P

ears

on e

t al

.

20

012

Surg

ery

R

ehab

ilit

atio

n

2.3

0 (

-3.4

0 t

o 7

.90

) -2

.40

(-1

6.9

0 t

o

12

.10)

Dis

abil

ity

(LT

), 0

to

10

0

4.7

0 (

-10

.55

to

19.9

5)

Sp

inal

sten

osi

s L

ater

al r

eces

s N

o l

ater

al r

eces

s P

ears

on e

t al

.

20

012

Surg

ery

R

ehab

ilit

atio

n

-1.8

0 (

-7.8

0 t

o 4

.20

) 2

.80

(-1

1.5

0 t

o

17

.10)

Dis

abil

ity

(ST

), 0

to

10

0

-4.6

0 (

-20

.33

to

11

.13)

Sp

inal

sten

osi

s L

ater

al r

eces

s N

o l

ater

al r

eces

s P

ears

on e

t al

.

20

012

Surg

ery

R

ehab

ilit

atio

n

2.5

0 (

-3.2

0 t

o 8

.20

) -3

.80

(-1

7.6

0 t

o

9.9

0)

Dis

abil

ity

(LT

), 0

to

10

0

6.3

0 (

-8.1

3 t

o 2

0.7

3)

Sp

inal

sten

osi

s

Neu

rofo

ram

in

al

No

neu

rofo

ram

inal

Pea

rso

n e

t al

.

20

012

Surg

ery

R

ehab

ilit

atio

n

-3.2

0 (

-12

.80

to

6.3

0)

-0.4

0 (

-6.9

0 t

o 6

.10

) D

isab

ilit

y

(ST

), 0

to

10

0

-2.8

0 (

-14

.33

to

8.7

3)

Sp

inal

sten

osi

s

Neu

rofo

ram

in

al

No

neu

rofo

ram

inal

Pea

rso

n e

t al

.

20

012

Surg

ery

R

ehab

ilit

atio

n

0.5

0 (

-8.8

0 t

o 9

.90

) 2

.00

(-4

.30

to

8.2

0)

Dis

abil

ity

(LT

), 0

to

10

0

-1.5

0 (

-12

.85

to

9.8

5)

Sp

inal

sten

osi

s S

ever

e

Mil

d/

mo

der

ate

Pea

rso

n e

t al

.

20

012

Surg

ery

R

ehab

ilit

atio

n

3.4

0 (

-4.1

0 t

o 1

0.9

0)

-5.6

0 (

-13

.40

to

2.2

0)

Dis

abil

ity

(ST

), 0

to

10

0

9.0

0 (

-1.8

7 t

o 1

9.8

7)

Sp

inal

sten

osi

s S

ever

e

Mil

d/

mo

der

ate

Pea

rso

n e

t al

.

20

012

Surg

ery

R

ehab

ilit

atio

n

3.4

0 (

-3.8

0 t

o 1

0.7

0)

-0.3

0 (

-7.9

0 t

o 7

.30

) D

isab

ilit

y

(LT

), 0

to

10

0

3.7

0 (

-6.8

5 t

o 1

4.2

5)

Sp

inal

sten

osi

s L

ater

al r

eces

s N

o l

ater

al r

eces

s A

rts

et a

l. 2

01

0

Tub

ula

r

dis

cect

om

y

Co

nven

tio

nal

mic

rod

isce

cto

my

0

.63

(0

.34

to

1.1

5)2

1

.03

(0

.80

to

1.3

2)2

Rec

over

y

(LT

), ≥

alm

ost

com

ple

te

reco

ver

y

1.6

4 (

0.8

5 t

o 3

.15)2

Dis

c hei

ght

≥7

mm

<

7m

m

Art

s et

al.

20

10

T

ub

ula

r

dis

cect

om

y

Co

nven

tio

nal

mic

rod

isce

cto

my

0

.92

(0

.71

to

1.1

8)2

1

.24

(0

.70

to

2.2

0)2

Rec

over

y

(LT

), ≥

alm

ost

com

ple

te

reco

ver

y

1.3

5 (

0.7

3 t

o 2

.52)2

Her

nia

tio

n/

sten

osi

s D

isc

pro

lap

se

Sp

inal

ste

no

sis

Taf

azal

et

al.

20

09

Bup

ivac

aine

+

ster

oid

B

up

ivac

aine

3.1

0 (

-11

.23

to

17

.43)

-1.3

0 (

-15

.21

to

17

.81)

Pai

n (

ST

), 0

to

10

0

4.4

0 (

-18

.13

to

26.9

3)

Her

nia

tio

n/

sten

osi

s D

isc

pro

lap

se

Sp

inal

ste

no

sis

Taf

azal

et

al.

20

09

Bup

ivac

aine

+

ster

oid

B

up

ivac

aine

-0.2

0 (

-9.3

4 t

o 9

.47

) -5

.00

(-3

.73

to

13

.73)

Dis

abil

ity

(ST

), 0

to

10

0

4.8

0 (

-9.0

6 t

o 1

8.6

6)

ST

=sh

ort

-ter

m (

0 t

o ≤

6m

onth

s);

LT

=lo

ng

-ter

m (

>6

mo

nth

s).

Mea

n d

iffe

rence

and

95

% C

I, p

osi

tive

valu

es

favo

rs t

reat

ment

effe

ct f

or

MR

I p

osi

tive

(+).

a S

tati

stic

all

y s

ignif

icant.

b V

alues

are

rep

rese

nte

d a

s o

dd

s ra

tio

s an

d 9

5%

co

nfi

den

ce i

nte

rvals

. A

n o

dd

rat

io g

reat

er t

han

1 f

avo

rs t

reat

men

t ef

fect

fo

r M

RI

po

siti

ve

(+).

c V

alues

are

rep

rese

nte

d a

s haz

ard

rat

io a

nd

95

% c

onfi

den

ce i

nte

rvals

. A

haz

ard

rat

io g

reat

er t

han

1 f

avo

rs t

reat

ment

eff

ect

fo

r M

RI

po

siti

ve

(+).

174

Appendix S1. Search strategy 1

MEDLINE via Ovid and Cochrane Central of Controlled trials via The Cochrane Library

1. (randomized controlled trial or controlled clinical trial or comparative study or clinical

trial or clinical trials or randomized or placebo$ or random allocation or random$ or

double-blind method or single-blind method).mp.

[mp=title, abstract, original title, name of substance word, subject heading word, keyword

heading word, protocol supplementary concept, rare disease supplementary concept,

unique identifier]

2. animal/ not human/

3. 1 not 2

4. (low back pain or back pain or back strain or simple back pain or non-specific back pain

or low back syndrome or low back dysfunction or lumbar pain or backache or lumbago or

sciatica or radiculopathy).mp.



unique identifier]

5. 3 and 4

6. (magnetic resonance imaging or mri or magnetic resonance or nmr or nuclear magnetic

resonance or disc degeneration or desiccation or loss of disc height or bulge or protrusion

or extrusion or nerve root compromise or annular tear or endplate changes or stenosis or

facet degeneration or high intensity zone or modic changes or degenerative disc disease or

spondylolisthesis).mp.



unique identifier]

7. 5 and 6

EMBASE (www.embase.com)

1. ‘randomized controlled trial’/exp OR ‘randomized controlled trial’ OR ‘controlled

study’/exp OR ‘controlled study’ OR ‘double blind procedure’/exp OR ‘double blind

procedure’ OR ‘placebo’/exp OR ‘placebo’ OR ‘random allocation’/exp OR ‘random

allocation’ OR ‘clinical trial’/exp OR ‘clinical trial’ OR ‘clinical trials’/exp OR ‘clinical

trials’ OR ‘double blind’ OR ‘single blind’

2. ‘animal’/exp OR ‘animal’ OR ‘not human’

3. #1 NOT #2

4. ‘low back pain’/exp OR ‘low back pain’ OR ‘back pain’/exp OR ‘back pain’ OR ‘lumbar

pain’/exp OR ‘lumbar pain’ OR ‘backache’/exp OR ‘backache’ OR ‘lumbago’/exp OR

‘lumbago’ OR ‘radiculopathy’/exp OR ‘radiculopathy’ Or ‘sciatic$’

5. #3 AND #4

6. 'magnetic resonance imaging'/exp OR 'magnetic resonance imaging' OR 'mri'/exp OR 'mri'

OR 'nuclear magnetic resonance'/exp OR 'nuclear magnetic resonance' OR 'nmr'/exp OR

'nmr' OR 'disc degeneration'/exp OR 'disc degeneration' OR 'desiccation'/exp OR

'desiccation' OR 'loss of disc height' OR 'bulge' OR 'protrusion' OR 'extrusion' OR 'nerve

root compression'/exp OR 'nerve root compression' OR 'annular tear' OR 'endplate changes'

OR 'stenosis'/exp OR 'stenosis' OR 'facet degeneration' OR 'high intensity zone' OR 'modic

changes' OR 'degenerative disc disease' OR 'spondylolisthesis'/exp OR 'spondylolisthesis'

7. #5 AND #6

175

Appendix S2. Search strategy 2

MEDLINE via Ovid and Cochrane Central of Controlled trials via The Cochrane

Library

1. (randomized controlled trial or controlled clinical trial or comparative study or

clinical trial or clinical trials or randomized or placebo$ or random allocation or

random$ or double-blind method or single-blind method).mp.

[mp=title, abstract, original title, name of substance word, subject heading word,

keyword heading word, protocol supplementary concept, rare disease supplementary

concept, unique identifier]

2. animal/ not human/

3. 1 not 2

4. (low back pain or back pain or back strain or simple back pain or non-specific back

pain or low back syndrome or low back dysfunction or lumbar pain or backache or

lumbago or sciatica or radiculopathy).mp.




5. 3 and 4

6. (target intervent$ or targeted treatment$ or subgroup$ or treatment effect or effect

mod$ or effect med$ or subgroup anal$).mp.




7. 5 and 6

EMBASE (www.embase.com)

1. ‘randomized controlled trial’/exp OR ‘randomized controlled trial’ OR ‘controlled

study’/exp OR ‘controlled study’ OR ‘double blind procedure’/exp OR ‘double blind

procedure’ OR ‘placebo’/exp OR ‘placebo’ OR ‘random allocation’/exp OR ‘random

allocation’ OR ‘clinical trial’/exp OR ‘clinical trial’ OR ‘clinical trials’/exp OR

‘clinical trials’ OR ‘double blind’ OR ‘single blind’

2. ‘animal’/exp OR ‘animal’ OR ‘not human’

3. #1 NOT #2

4. ‘low back pain’/exp OR ‘low back pain’ OR ‘back pain’/exp OR ‘back pain’ OR

‘lumbar pain’/exp OR ‘lumbar pain’ OR ‘backache’/exp OR ‘backache’ OR

‘lumbago’/exp OR ‘lumbago’ OR ‘radiculopathy’/exp OR ‘radiculopathy’ Or

‘sciatic$’

5. #3 AND #4

6. 'target intervent$' OR 'targeted treatment$' OR 'subgroup$' OR 'treatment effect' OR

'effect mod$' OR 'effect med$' OR 'subgroup anal$'

7. #5 AND #6

176

Appendix S3. Criteria list for the risk of bias assessment

1) Randomization: A random (unpredictable) assignment sequence. Examples of adequate methods are

coin toss (for studies with 2 groups), rolling a dice (for studies with 2 or more groups), drawing of balls

of different colors, drawing of ballots with the study group labels from a dark bag, computer-generated

random sequence, pre-ordered sealed envelopes, sequentially-ordered vials, telephone call to a central

office, and pre-ordered list of treatment assignments Examples of inadequate methods are: alternation,

birth date, social insurance/ security number, date in which they are invited to participate in the study,

and hospital registration number.

2) Concealed allocation: Assignment generated by an independent person not responsible for

determining the eligibility of the patients. This person has no information about the persons included in

the trial and has no influence on the assignment sequence or on the decision about eligibility of the

patient.

3) Participant blinding: This item should be scored “yes” if the index and control groups are

indistinguishable for the patients or if the success of blinding was tested among the patients and it was

successful.

4) Clinicians blinding: This item should be scored “yes” if the index and control groups are

indistinguishable for the care providers or if the success of blinding was tested among the care providers

and it was successful.

5) Outcome assessor blinding: Adequacy of blinding should be assessed for the primary outcomes. This

item should be scored “yes” if the success of blinding was tested among the outcome assessors and it was

successful or:

–for patient-reported outcomes in which the patient is the outcome assessor (e.g., pain, disability): the

blinding procedure is adequate for outcome assessors if participant blinding is scored “yes”;

–for outcome criteria assessed during scheduled visit and that supposes a contact between participants

and outcome assessors (e.g., clinical examination): the blinding procedure is adequate if patients are

blinded, and the treatment or adverse effects of the treatment cannot be noticed during clinical

examination;

–for outcome criteria that do not suppose a contact with participants (e.g., radiography, magnetic

resonance imaging): the blinding procedure is adequate if the treatment or adverse effects of the

treatment cannot be noticed when assessing the main outcome;

–for outcome criteria that are clinical or therapeutic events that will be determined by the interaction

between patients and care providers (e.g., co-interventions, hospitalization length, treatment failure), in

which the care provider is the outcome assessor: the blinding procedure is adequate for outcome

assessors if item “4” (caregivers) is scored “yes”;

–for outcome criteria that are assessed from data of the medical forms: the blinding procedure is adequate

if the treatment or adverse effects of the treatment cannot be noticed on the extracted data.

6) Acceptable drop-out rate: The number of participants who were included in the study but did not

complete the observation period or were not included in the analysis must be described and reasons

given. If the percentage of withdrawals and drop outs does not exceed 20% for short-term follow up and

30% for long-term follow up and does not lead to substantial bias a “yes” is scored. (N.B. these

percentages are arbitrary, not supported by literature).

7) Analysed according to treatment allocation: All randomized patients are reported/analyzed in the

group they were allocated to by randomization for the most important moments of effect measurement

(minus missing values) irrespective of non-compliance and co-interventions.

8) Free of selective outcomes: In order to receive a “yes”, the review author determines if all the results

from all pre-specified outcomes have been adequately reported in the published report of the trial. This

information is either obtained by comparing the protocol and the report, or in the absence of the protocol,

assessing that the published report includes enough information to make this judgment.

9) Baseline similarity: In order to receive a “yes”, groups have to be similar at baseline regarding

demographic factors, duration and severity of complaints, percentage of patients with neurological

177

symptoms, and value of main outcome measure(s).

10) Co-interventions: This item should be scored “yes” if there were no co-interventions or they were

similar between the index and control groups.

11) Compliance: The reviewer determines if the compliance with the interventions is acceptable, based

on the reported intensity, duration, number and frequency of sessions for both the index intervention and

control intervention(s). For example, physiotherapy treatment is usually administered over several

sessions; therefore it is necessary to assess how many sessions each patient attended. For single session

interventions (e.g., surgery), this item is irrelevant.

12) Outcome timing: Timing of outcome assessment should be identical for all intervention groups and

for all important outcome assessments.

178

Ap

pen

dix

S4.

Lis

t of

excl

uded

full

-tex

t ar

ticl

es a

nd t

he

pri

mar

y r

easo

n f

or

excl

usi

on.

Stu

dy

Tit

le

Fir

st r

easo

n f

or

excl

ud

ing

Ack

erm

an, S

. J.

, et

al.

1997

Per

sist

ent

low

bac

k p

ain i

n p

atie

nts

susp

ecte

d o

f h

avin

g h

ernia

ted n

ucl

eus

pulp

osu

s:

Rad

iolo

gic

pre

dic

tors

of

funct

ional

outc

om

e -

Imp

lica

tions

for

trea

tmen

t se

lect

ion

N

ot

an R

CT

Ahn, S

. H

., e

t al

. 2002

C

om

par

ison o

f cl

inic

al o

utc

om

es a

nd n

atura

l m

orp

holo

gic

ch

anges

bet

wee

n

seques

tere

d a

nd l

arge

centr

al e

xtr

uded

dis

c her

nia

tions

Not

an R

CT

Alb

ert,

H. B

., e

t al

. 2013

Anti

bio

tic

trea

tmen

t in

pat

ients

wit

h c

hro

nic

low

bac

k p

ain a

nd v

erte

bra

l b

one

edem

a (M

odic

typ

e 1 c

han

ges

): a

double

-bli

nd r

andom

ized

cli

nic

al c

ontr

oll

ed t

rial

of

effi

cacy

Not

poss

ible

to e

luci

dat

e

asso

ciat

ion b

etw

een M

RI

and

outc

om

e

Art

s, M

. P

., e

t al

. 2011

Tubula

r dis

kec

tom

y v

s co

nven

tional

mic

rodis

kec

tom

y f

or

the

trea

tmen

t o

f lu

mbar

dis

k h

ernia

tion:

2-Y

ear

resu

lts

of

a double

-bli

nd r

andom

ized

contr

oll

ed t

rial

Not

poss

ible

to e

luci

dat

e

asso

ciat

ion b

etw

een M

RI

and

outc

om

e

Bro

uw

er, P

. A

., e

t al

.

2009

Eff

ecti

ven

ess

of

per

cuta

neo

us

lase

r dis

c d

ecom

pre

ssio

n v

ersu

s co

nven

tional

open

dis

cect

om

y i

n t

he

trea

tmen

t of

lum

bar

dis

c her

nia

tion;

des

ign o

f a

pro

spec

tive

random

ized

contr

oll

ed t

rial

Not

an R

CT

Bro

wd

er, D

. A

., e

t al

.

2007

Eff

ecti

ven

ess

of

an e

xte

nsi

on

-ori

ente

d t

reat

men

t ap

pro

ach i

n a

sub

gro

up o

f su

bje

cts

wit

h l

ow

bac

k p

ain:

a ra

ndom

ized

cli

nic

al t

rial

No e

val

uat

ion o

f M

RI

findin

gs

Bro

wn,

L.

L. 2012

A d

ouble

-bli

nd, ra

ndom

ized

, pro

spec

tive

stud

y o

f ep

idura

l st

eroid

inje

ctio

n v

s. t

he

mil

d p

roce

dure

in p

atie

nts

wit

h s

ym

pto

mat

ic l

um

bar

spin

al s

tenosi

s

Not

poss

ible

to e

luci

dat

e

asso

ciat

ion b

etw

een M

RI

and

outc

om

e

Bro

x, J.

I., e

t al

. 2010

Four-

yea

r fo

llow

up o

f su

rgic

al v

ersu

s non

-surg

ical

ther

apy f

or

chro

nic

low

bac

k

pai

n

Not

poss

ible

to e

luci

dat

e

asso

ciat

ion b

etw

een M

RI

and

outc

om

e

Bro

x, J.

I., e

t al

. 2003

Ran

dom

ized

cli

nic

al t

rial

of

lum

bar

inst

rum

ente

d f

usi

on

and c

ognit

ive

inte

rven

tion

and e

xer

cise

s in

pat

ients

wit

h c

hro

nic

low

bac

k p

ain a

nd d

isc

deg

ener

atio

n

Not

poss

ible

to e

luci

dat

e

asso

ciat

ion b

etw

een M

RI

and

outc

om

e

Chil

ds,

J. D

., e

t al

. 2004

A

cli

nic

al p

redic

tion r

ule

to i

den

tify

pat

ients

wit

h l

ow

bac

k p

ain m

ost

lik

ely t

o

ben

efit

fro

m s

pin

al m

anip

ula

tion:

a val

idat

ion s

tud

y

No e

val

uat

ion o

f M

RI

findin

gs

Erg

inou

sakis

, D

., e

t al

.

2011

Com

par

ativ

e pro

spec

tive

random

ized

stu

dy c

om

par

ing c

onse

rvat

ive

trea

tmen

t an

d

per

cuta

neo

us

dis

k d

ecom

pre

ssio

n f

or

trea

tmen

t of

inte

rver

tebra

l dis

k h

ernia

tion

Not

poss

ible

to e

luci

dat

e

asso

ciat

ion b

etw

een M

RI

and

outc

om

e

Fil

iz, M

., e

t al

. 2005

T

he

effe

ctiv

enes

s of

exer

cise

pro

gra

mm

es a

fter

lum

bar

dis

c su

rger

y:

a ra

nd

om

ized

N

ot

poss

ible

to e

luci

dat

e

179

contr

oll

ed s

tud

y

asso

ciat

ion b

etw

een M

RI

and

outc

om

e

Fre

bu

rger

, J.

K., e

t al

.

2006

Eff

ecti

ven

ess

of

ph

ysi

cal

ther

apy f

or

the

man

agem

ent

of

chro

nic

spin

e dis

ord

ers:

A

pro

pen

sity

sco

re a

ppro

ach

N

ot

an R

CT

Fri

tz, J.

M., e

t al

. 2007

Is t

her

e a

sub

gro

up o

f pat

ients

wit

h l

ow

bac

k p

ain l

ikel

y t

o b

enef

it f

rom

mec

han

ical

trac

tion? R

esult

s of

a ra

ndom

ized

cli

nic

al t

rial

and s

ubgro

upin

g a

nal

ysi

s

No e

val

uat

ion o

f M

RI

findin

gs

Fri

tzel

l, P

., e

t al

. 2001

Lum

bar

fu

sion

ver

sus

no

nsu

rgic

al t

reat

men

t fo

r ch

ronic

low

bac

k p

ain. A

mult

icen

ter

random

ized

contr

oll

ed t

rial

fro

m t

he

Sw

edis

h L

um

bar

Spin

e S

tud

y

Gro

up

Not

poss

ible

to e

luci

dat

e

asso

ciat

ion b

etw

een M

RI

and

outc

om

e

Fri

tzel

l, P

., e

t al

. 2002

Chro

nic

low

bac

k p

ain a

nd f

usi

on:

A c

om

par

ison o

f th

ree

surg

ical

tec

hniq

ues

: A

pro

spec

tive

mult

icen

ter

random

ized

stu

dy f

rom

th

e S

wed

ish L

um

bar

Spin

e S

tud

y

Gro

up

Not

poss

ible

to e

luci

dat

e

asso

ciat

ion b

etw

een M

RI

and

outc

om

e

Fro

hold

t, A

., e

t al

. 2011

No d

iffe

rence

in l

on

g-t

erm

tru

nk m

usc

le s

tren

gth

, cr

oss

-sec

tional

are

a, a

nd d

ensi

ty

in p

atie

nts

wit

h c

hro

nic

low

bac

k p

ain 7

to 1

1 y

ears

aft

er l

um

bar

fusi

on

ver

sus

cognit

ive

inte

rven

tion a

nd e

xer

cise

s

Not

poss

ible

to e

luci

dat

e

asso

ciat

ion b

etw

een M

RI

and

outc

om

e

Gore

n, A

., e

t al

. 2010

Eff

icac

y o

f ex

erci

se a

nd u

ltra

sound i

n p

atie

nts

wit

h l

um

bar

spin

al s

tenosi

s: a

pro

spec

tive

random

ized

contr

oll

ed t

rial

Not

poss

ible

to e

luci

dat

e

asso

ciat

ion b

etw

een M

RI

and

outc

om

e

Gudav

alli

, M

. R

., e

t al

.

2006

A r

andom

ized

cli

nic

al t

rial

and s

ub

gro

up a

nal

ysi

s to

com

par

e fl

exio

n-d

istr

acti

on

wit

h a

ctiv

e ex

erci

se f

or

chro

nic

low

bac

k p

ain

Not

poss

ible

to e

luci

dat

e

asso

ciat

ion b

etw

een M

RI

and

outc

om

e

Hel

lum

, C

., e

t al

. 2011

Surg

ery w

ith d

isc

pro

sth

esis

ver

sus

reh

abil

itat

ion i

n p

atie

nts

wit

h l

ow

bac

k p

ain a

nd

deg

ener

ativ

e dis

c: t

wo y

ear

foll

ow

-up o

f ra

ndom

ised

stu

dy

Not

poss

ible

to e

luci

dat

e

asso

ciat

ion b

etw

een M

RI

and

outc

om

e

Hem

mil

a, H

. M

., e

t al

.

2002

Lon

g-t

erm

eff

ecti

ven

ess

of

bone-

sett

ing, li

ght

exer

cise

ther

apy, an

d p

hysi

oth

erap

y

for

pro

lon

ged

bac

k p

ain:

a ra

ndom

ized

contr

oll

ed t

rial

Not

poss

ible

to e

luci

dat

e

asso

ciat

ion b

etw

een M

RI

and

outc

om

e

Huda,

N., e

t al

. 2010

The

effi

cacy o

f ep

idura

l dep

o-m

eth

ylp

rednis

olo

ne

and t

riam

cino

lone

acet

ate

in

reli

evin

g t

he

sym

pto

ms

of

lum

bar

can

al s

tenosi

s: A

com

par

ativ

e st

ud

y

Not

poss

ible

to e

luci

dat

e

asso

ciat

ion b

etw

een M

RI

and

outc

om

e

Hurr

i, H

., e

t al

. 1998

L

um

bar

spin

al s

tenosi

s: a

sses

smen

t of

long-t

erm

outc

om

e 12 y

ears

aft

er o

per

ativ

e

and c

onse

rvat

ive

trea

tmen

t N

ot

an R

CT

180

Jense

n, R

. K

., e

t al

. 2012

Res

t ver

sus

exer

cise

as

trea

tmen

t fo

r p

atie

nts

wit

h l

ow

bac

k p

ain a

nd M

odic

chan

ges

. A

ran

dom

ized

contr

oll

ed c

linic

al t

rial

Not

poss

ible

to e

luci

dat

e

asso

ciat

ion b

etw

een M

RI

and

outc

om

e

Kaa

pa,

E., e

t al

. 2012

Corr

elat

ion o

f si

ze a

nd t

ype

of

Modic

types

1 a

nd 2

les

ions

wit

h c

linic

al s

ym

pto

ms:

a des

crip

tiv

e st

ud

y i

n a

subgro

up o

f pat

ients

wit

h c

hro

nic

low

bac

k p

ain o

n t

he

bas

is

of

a univ

ersi

ty h

osp

ital

pat

ient

sam

ple

Not

an R

CT

Kaw

u, A

. A

., e

t al

. 2011

F

acet

join

ts i

nfi

ltra

tion:

A v

iable

alt

ern

ativ

e tr

eatm

ent

to p

hysi

oth

erap

y i

n p

atie

nts

wit

h l

ow

bac

k p

ain d

ue

to f

acet

join

t ar

thro

pat

hy

Not

an R

CT

Ken

ned

y, D

. J.

, et

al.

2013

Mult

icen

ter

random

ized

contr

oll

ed t

rial

com

par

ing p

arti

cula

te v

ersu

s nonp

arti

cula

te

cort

icost

eroid

s v

ia l

um

bar

tra

nsf

ora

min

al e

pid

ura

l in

ject

ion f

or

acute

unil

ater

al,

unil

evel

rad

icula

r pai

n d

ue

to h

ernia

ted n

ucl

eus

pulp

osu

s

Not

poss

ible

to e

luci

dat

e

asso

ciat

ion b

etw

een M

RI

and

outc

om

e

Koc,

Z., e

t al

. 2009

Eff

ecti

ven

ess

of

ph

ysi

cal

ther

apy a

nd e

pid

ura

l st

eroid

inje

ctio

ns

in l

um

bar

spin

al

sten

osi

s

Not

poss

ible

to e

luci

dat

e

asso

ciat

ion b

etw

een M

RI

and

outc

om

e

Koes

, B

. W

., e

t al

. 1993

A

ran

dom

ized

cli

nic

al t

rial

of

man

ual

ther

apy a

nd p

hysi

oth

erap

y f

or

per

sist

ent

bac

k

and n

eck c

om

pla

ints

: S

ubgro

up a

nal

ysi

s an

d r

elat

ionsh

ip b

etw

een o

utc

om

e m

easu

res

No e

val

uat

ion o

f M

RI

findin

gs

Lon

g, A

., e

t al

. 2004

D

oes

it

mat

ter

whic

h e

xer

cise

? A

ran

dom

ized

contr

ol

tria

l of

exer

cise

for

low

bac

k

pai

n

No e

val

uat

ion o

f M

RI

findin

gs

Mal

miv

aara

, A

., e

t al

.

2007

Surg

ical

or

nonoper

ativ

e tr

eatm

ent

for

lum

bar

spin

al s

tenosi

s? A

ran

dom

ized

contr

oll

ed t

rial

Not

poss

ible

to e

luci

dat

e

asso

ciat

ion b

etw

een M

RI

and

outc

om

e

Med

rik

-Gold

ber

g,

T., e

t

al. 1999

Intr

aven

ous

lidoca

ine,

am

anta

din

e, a

nd p

lace

bo i

n t

he

trea

tmen

t of

scia

tica

: A

double

-bli

nd, ra

ndom

ized

, co

ntr

oll

ed s

tud

y

Not

poss

ible

to e

luci

dat

e

asso

ciat

ion b

etw

een M

RI

and

outc

om

e

Ost

erm

an, H

., e

t al

. 2006

Eff

ecti

ven

ess

of

mic

rodis

cect

om

y f

or

lum

bar

dis

c her

nia

tion:

a ra

ndom

ized

contr

oll

ed t

rial

wit

h 2

year

s of

foll

ow

-up

Not

poss

ible

to e

luci

dat

e

asso

ciat

ion b

etw

een M

RI

and

outc

om

e

Pen

g,

B., e

t al

. 2009

D

iagnosi

s an

d s

urg

ical

tre

atm

ent

of

bac

k p

ain o

rigin

atin

g f

rom

endpla

te

Not

an R

CT

Rad

clif

f, K

., e

t al

. 2011

D

oes

opio

id p

ain m

edic

atio

n u

se a

ffec

t th

e outc

om

e of

pat

ients

wit

h l

um

bar

dis

c

her

nia

tion? A

subgro

up a

nal

ysi

s of

the

SP

OR

T s

tud

y

No e

val

uat

ion o

f M

RI

findin

gs

Raj

asek

aran

, S

., e

t al

.

2013

Lum

bar

spin

ous

pro

cess

spli

ttin

g d

ecom

pre

ssio

n p

rovid

es e

quiv

alen

t outc

om

es t

o

conven

tional

mid

line

dec

om

pre

ssio

n i

n d

egen

erat

ive

lum

bar

can

al s

tenosi

s: A

Not

poss

ible

to e

luci

dat

e

asso

ciat

ion b

etw

een M

RI

and

181

pro

spec

tive,

ran

dom

ised

contr

oll

ed s

tud

y o

f 51 p

atie

nts

outc

om

e

San

till

i, V

., e

t al

. 20

06

Chir

opra

ctic

man

ipula

tio

n i

n t

he

trea

tmen

t of

acute

bac

k p

ain a

nd s

ciat

ica

wit

h d

isc

pro

trusi

on:

a ra

ndom

ized

double

-bli

nd c

linic

al t

rial

of

acti

ve

and s

imula

ted s

pin

al

man

ipula

tions

Not

poss

ible

to e

luci

dat

e

asso

ciat

ion b

etw

een M

RI

and

outc

om

e

Sher

man

, K

. J.

, et

al.

2009

Char

acte

rist

ics

of

pat

ients

wit

h c

hro

nic

bac

k p

ain w

ho b

enef

it f

rom

acu

pun

cture

N

o e

val

uat

ion o

f M

RI

findin

gs

Sla

tis,

P., e

t al

. 2011

Lon

g-t

erm

res

ult

s of

surg

ery f

or

lum

bar

spin

al s

tenosi

s: a

ran

dom

ised

contr

oll

ed

tria

l

Not

poss

ible

to e

luci

dat

e

asso

ciat

ion b

etw

een M

RI

and

outc

om

e

Ste

enst

ra,

I. A

., e

t al

.

2009

What

work

s bes

t fo

r w

ho

m? A

n e

xplo

rato

ry, su

bgro

up a

nal

ysi

s in

a r

ando

miz

ed,

contr

oll

ed t

rial

on t

he

effe

ctiv

enes

s of

a w

ork

pla

ce i

nte

rven

tion i

n l

ow

bac

k p

ain

pat

ients

on

ret

urn

to w

ork

Not

poss

ible

to e

luci

dat

e

asso

ciat

ion b

etw

een M

RI

and

outc

om

e

Sty

czynsk

i, T

., e

t al

.

2007

The

effe

ct o

f th

e gra

de

of

deg

ener

ativ

e ch

anges

in t

he

spin

e on t

he

outc

om

es o

f

surg

ery f

or

lum

bar

dis

copat

hy w

ith a

rad

icula

r sy

ndro

me

Not

an R

CT

Under

wood, M

. R

., e

t al

.

2007

Do b

asel

ine

char

acte

rist

ics

pre

dic

t re

sponse

to t

reat

men

t fo

r lo

w b

ack p

ain

?

Sec

ondar

y a

nal

ysi

s of

the

UK

BE

AM

dat

aset

No e

val

uat

ion o

f M

RI

findin

gs

Voll

enbro

ek-H

utt

en, M

.

M., e

t al

. 2004

Dif

fere

nce

s in

outc

om

e o

f a

mult

idis

cipli

nar

y t

reat

men

t bet

wee

n s

ub

gro

ups

of

chro

nic

low

bac

k p

ain p

atie

nts

def

ined

usi

ng t

wo m

ult

iaxia

l as

sess

men

t in

stru

men

ts:

the

mult

idim

ensi

onal

pai

n i

nven

tory

and l

um

bar

dyn

amom

etry

No e

val

uat

ion o

f M

RI

findin

gs

Wil

ken

s, P

., e

t al

. 2012

No e

ffec

t of

6-m

onth

inta

ke

of

glu

cosa

min

e su

lfat

e on M

odic

chan

ges

or

hig

h

inte

nsi

ty z

ones

in t

he

lum

bar

spin

e: s

ub

-gro

up a

nal

ysi

s of

a ra

ndom

ized

co

ntr

oll

ed

tria

l

Not

poss

ible

to e

luci

dat

e

asso

ciat

ion b

etw

een M

RI

and

outc

om

e

Zhuo, X

., e

t al

. 2010

Eff

ecti

ven

ess

com

par

ison o

f tw

o s

urg

ical

pro

cedu

res

on l

um

bar

dis

c pro

tru

sion

N

ot

an R

CT

182

Chapter Nine

Influence of clinician characteristics and operational factors on recruitment of

participants with low back pain: an observational study

Chapter Nine published as:

Steffens D, Maher CG, Ferreira ML, Hancock MJ, Pereira LSM, Williams CM, Latimer J.

Influence of clinician characteristics and operational factors on recruitment of participants

with low back pain: an observational study. Journal of Manipulative Physiological

Therapeutics. 2014; 38:151-158.

183


As co-authors of the paper “Influence of clinician characteristics and operational factors

on recruitment of participants with low back pain: an observational study”, we confirm that

Daniel Steffens has made the following contributions:


Data collection







Christopher M Williams Date: 01.01.2015


184

185

INFLUENCE OF CLINICIAN CHARACTERISTICS AND

OPERATIONAL FACTORS ON RECRUITMENT OF

PARTICIPANTS WITH LOW BACK PAIN: AN

OBSERVATIONAL STUDY

Daniel Steffens, BPT (Hons), a, b Chris G. Maher, PhD, c Manuela L. Ferreira, PhD, d Mark J. Hancock, PhD, eLeani S.M. Pereira, PhD, f Christopher M. Williams, PhD, g and Jane Latimer, PhDc

ABSTRACT

a PhD Student,lobal Health, Syydney, Australiab PhD Student,

f Minas Gerais,c Professor, Mlobal Health, Syydney, Australiad Senior Reseastitute for Globaf Sydney, Sydnee Senior Lectuuman Sciencesf Professor, Deinas Gerais, Be

Objective: The purpose of this study was to identify factors that influence recruitment of patients to an observationalstudy of low back pain (LBP).Methods: From 1147 primary care (first health contact) clinicians initially contacted, 138 (physiotherapists andchiropractors) agreed to participate in a large observational study of LBP and were the focus of the current study. Datawere collected pertaining to clinicians' characteristics, operational factors, and the number of patients recruited. Theassociation of a variety of clinician characteristics and operational factors with recruitment rate was determined using amultivariate negative binomial regression analysis.Results: From October 2011 to November 2012, 1585 patients were screened by 138 study clinicians with 951 eligiblepatients entering the observational study. Clinicians who were members of their professional association had a recruitmentrate less than half that of those who were nonmembers (P b .0001). Clinicians who were trained by telephone had arecruitment rate 4.01 times higher than those trained face to face (P b .0001). Similarly, clinicians who referred a largernumber of ineligible participants had a slightly higher recruitment rate with an incident rate ratio of 1.04 per ineligiblepatient (P b .0001). Other clinicians' characteristics and operational factors were not associated with recruitment.Conclusion: This study provides evidence that it is feasible to recruit participants from primary care practices to asimple observational study of LBP. Factors identified as influencing recruitment were professional association(negative association), training by telephone, and referring a higher number of ineligible participants. (J ManipulativePhysiol Ther 2015;xx:1-8)
Key Indexing Terms: Patient Selection; Back Pain; Primary Health Care; Physical Therapy; Chiropractic
Participant recruitment is one of the most challengingphases of the research process and may cause studiesto become unfeasible.1,2 It is estimated that 85% of

Musculoskeletal Division, The George Institute fordney Medical School, The University of Sydney,.Department of Physiotherapy, Federal UniversityBelo Horizonte, Brazil.usculoskeletal Division, The George Institute fordney Medical School, The University of Sydney,.rch Fellow,Musculoskeletal Division, The Georgel Health, Sydney Medical School, The Universityy, Australia.rer, Discipline of Physiotherapy, Faculty of, Macquarie University, Sydney, Australia.partment of Physiotherapy, Federal University oflo Horizonte, Brazil.

g Research Fellow, Hunter Medical Research Institute, Schoolof Medicine and Public Health, University of Newcastle,Newcastle, Australia.

Submit requests for reprints to: Daniel Steffens, BPT(Hons), PhD Student, Musculoskeletal Division, The GeorgeInstitute for Global Health, Sydney Medical School, TheUniversity of Sydney, PO Box M201, Missenden Road, Sydney,New South Wales, 2050, Australia. (e-mail: [email protected]).

Paper submitted April 11, 2014; in revised form October 1,2014; accepted October 10, 2014.

0161-4754Copyright © 2014 by National University of Health

Sciences.http://dx.doi.org/10.1016/j.jmpt.2014.10.016

GS

o

GS

Ino

H

M

studies do not conclude on schedule due to low participation,60% to 80% of studies do not meet their chronologicalendpoint because of challenges in recruitment, and 30% of



http://dx.doi.org/10.1016/j.jmpt.2014.10.016

2 Journal of Manipulative and Physiological TherapeuticsSteffens et alMonth 2015Factors Predicting Recruitment of Participants

186

study sites fail to recruit even a single participant.1,3,4

Unsatisfactory and/or untimely participant recruitment hasserious consequences, leading to an underpowered study,increased resource use and higher costs.5-7 Importantly, theintegrity and validity of the study also rely on obtaining anadequate sample size, and failure to achieve this may cause astudy with inconclusive findings.8

Most previous studies have focused on investigating factorsthat increase recruitment to randomized controlled trials(RCTs).3-5,7,9-12 Although RCTs are considered the “goldstandard” of study design,13 not all scientific questions can beanswered with this design. Researchers are often interested inquestions regarding etiology and prognosis, which may bebetter answered using an observational study design. Many ofthe barriers encountered when recruiting participants to RCTsmay be similar to those encountered when conductingobservational studies; however, factors affecting recruitmentto observational studies have not been carefully evaluated.14

Previous studies have identified reasons clinicians do notenroll eligible patients into clinical trials.15,16 Although thesereasons have been identified predominantly from studiesevaluating general practitioners, it is likely that many alsoapply to allied health practitioners (physiotherapists andchiropractors) who are operating as first contact practitionerfor patients presenting with back pain. These reasons includedifficulty for practitioners in following the study protocol andcompleting the recruitment process and patient preference fora certain therapy and difficulties obtaining informed consentfrom patients. In primary care, these recruitment barriers areoften heightened by the clinician's lack of time, whichsignificantly affects their ability to recruit participants.17

Other factors reported to influence recruitment of patientsinclude the importance of the research question, the simplicityof the research design, and ease of access to treatment.Financial reimbursement has been suggested as a possiblefactor10,18,19; however, a recent systematic review found that,in randomized controlled trials, reimbursement for time spenton recruitment is not associated with better recruitment.20 Inaddition, it is possible that recruiting fromhealth professionalsother than general practitioners such as physiotherapists andchiropractors may produce a different outcome. Regardless,recruitment of patients in primary care remains a significantissue.5,7 Therefore, studies that use simple recruitmentstrategies, minimal clinical involvement, and health profes-sionals other than general practitioners may have anadvantage in recruiting patients in primary care settings.

The reasons certain studies recruit successfully whileothers do not remain unclear.21 A better understanding ofclinicians' characteristics and the study operational charac-teristics (eg, method of training and type and number ofcontacts) may lead researchers to identify study strategiesassociated with recruitment of a larger number ofparticipants. Therefore, the aim of this study was to identifyfactors that influence recruitment to an observational studyof triggers for low back pain (LBP).

METHODS

DesignThis observational study investigated primary care

clinicians enrolling patients with acute LBP to a case-cross-over study (TRIGGERS). Participants were recruited fromOctober 2011 to November 2012. The methods andprocedures for recruitment of patients to the TRIGGERSstudy have been published elsewhere.22 Participants in theTRIGGERS study (n = 999)were also eligible to enroll in thePACE clinical trial. 23 The PACE clinical trial is adouble-blind placebo-controlled trial assessing the effectthat paracetamol has on recovery from acute nonspecific LBP.The inclusion criteria for the TRIGGERS and PACE studieswere similar; therefore, patients recruited for the PACEclinical trial could also be enrolled in the TRIGGERS study.However, data collected from recruiting clinicians (eg,personal information) and the study operational procedureswere different for both studies. Therefore, we reported thedata collected from participants who enrolled in theTRIGGERS study only (n = 951). Ethical approval for thestudy was granted by the University of Sydney HumanResearch Ethics Committee (protocol no. 05-2011/13742).

ParticipantsTRIGGERS recruited patients seeking care for LBP in

primary care clinics across Sydney, Australia. Eligibleparticipants met the following inclusion criteria: (1) compre-hends spoken English, (2) main complaint of LBP with orwithout leg pain (pain between 12th rib and buttock crease),(3) current episode of back pain less than or equal to 7 daysduration, (4) new episode (preceded by at least 1 monthwithout LBP), (5) pain of at leastmoderate intensity during thefirst 24 hours of this episode (scored on a 6-point scale fromnone to very severe). The exclusion criterion was confirmedor suspected serious spinal pathology (ie, cancer, fracture,and infection).

Clinician RecruitmentPrimary care clinicians were recruited for this study. In

Australia, primary care clinicians are those registered toprovide the first health contact for patients presenting fromthe community and include general practitioners, practicenurses, psychologists, physiotherapists, chiropractors, andpharmacists.24 According to the original protocol, generalpractitioners and pharmacists would be contacted to aidrecruitment. However, no attempts were made to recruitgeneral practitioners or pharmacists as adequate numbers ofpatients were recruited through physiotherapists and chiro-practors. In this study, the recruiting primary care clinicianswere physiotherapists and chiropractors.

Lists of physiotherapistsworking in Sydneywere acquiredfrom their association's Web site. All physiotherapists drawnfrom theAustralian PhysiotherapyAssociation databasewere

3Steffens et alJournal of Manipulative and Physiological TherapeuticsFactors Predicting Recruitment of ParticipantsVolume xx, Number x

187

members of the association. Thirty-five physiotherapists whoparticipated in the study were not members of the AustralianPhysiotherapy Association and were identified by theircolleagues (who were members and received our invitation).The chiropractors were selected from aGoogle search. A totalof 1147 clinicians (39 chiropractors and 1108 physiothera-pists) were invited to participate by letter. The letter outlinedthe study aims, sample size, inclusion/exclusion criteria, andthe benefits to the clinician and patient of participation.Interested clinicianswere invited to contact the study researchteam to obtain further information.A study researcher phonedthose who responded to further explain the study procedures.Additional training was provided for clinicians interested inrecruiting to the study. A total of 138 clinicians (135physiotherapists and 3 chiropractors) agreed to participate inthe study.

Training MethodsAfter confirming their interest in recruiting, clinicians

were offered 2methods of training: (1) face-to-face training attheir clinics or (2) training by a telephone call. The method oftraining was selected by the clinician.

Face-to-Face TrainingClinicians who chose face-to-face training were visited

and trained by an experienced research assistant at their ownpractice. Face-to-face training was supplemented withdistribution of a paper copy of the study protocol. Trainingtook around 30 minutes and was done in a group of up to 5clinicians working at the same practice.

Training by Telephone CallClinicianswho chose telephone training received their hard

copy of the study protocol by post approximately 1 weekbefore their telephone training call was scheduled. The callswere made by a research assistant and covered all the topics inthe face-to-face training. This training took around 30 minutesand was done individually.

Features Covered in Both Training MethodsIrrespective of whether the clinician chose face-to-face or

telephone training, the following topics were covered duringtraining: study background, aims, screening form (inclusion/exclusion criteria—refer to supplementary material forfurther details), informed consent form, referring patients(providing patient contact information to the research team),terms and conditions, human ethics, and study benefits.Clinicians could opt out at any time during the study period.

Screening PatientsClinicians were asked to screen for eligibility all (ie,

consecutive) patients who presented with LBP. Clinicians

were instructed to fax screening forms for both eligible andineligible patients to the study researchers as soon as theforms were completed. For those participants agreeing to beinvolved, consent forms were signed by the participants andclinicians at the participating sites.

ReimbursementClinicians were reimbursed AU $99 per eligible patient

referred to the study. This sum was used to cover theclinician's time spent in recruiting participants, explaining thestudy to them, and liaising with the study staff. Clinicianswere also reimbursed AU $10 per ineligible patient screened,to cover clerical and administration costs. Participants werereimbursed with AU $50 gift card for the time spentanswering the questions and to cover the cost of the mobiletelephone calls to the researcher. The typical duration of theinterview was approximately 30 minutes.

Clinician's Characteristics and Data CollectionPersonal information from the recruiting clinicians was

collected, including sex, date of birth, practice details(location/postcode), profession, current position, years ofpractice, years managing LBP, and whether the clinician wasa member of their professional association. All contacts madebetween the study researchers and the clinicians were enteredinto a database. Contacts were classified as phone call, letter,or e-mails.

Recruitment Outcome and Recruitment Predictor VariablesThe recruitment outcome was the total number of eligible

patients recruited by each individual clinician by the end ofthe study. Eligible patients were patients referred by theclinician successfully enrolled in the TRIGGERS study.

Although the prediction of recruitment study wasconceived after the main TRIGGERS study commenced,the recruitment predictor variables and analysis were defineda priori as presented in the manuscript. Clinicians' characte-ristics included (1) sex (male/female), (2) age (years), (3)suburb socioeconomic status (determined by comparing theclinic postcode to Australia Bureau of Statistics data oneconomic advantage and disadvantage by postcode anddichotomized into high ≥AU $577 or low socioeconomicstatus bAU $577, based on the average individual weeklyincome), (4) profession (physiotherapist or chiropractor), (5)clinical experience as practicing clinician (years), (6) clinicalexperience managing LBP (years), (7) current position(employee or business owner), and (8) professional associa-tionmembership status (member or not member). Operationalfactors included (1) trainingmethod (face-to-face or telephonecall), (2) number of letters (total number of letters sent to theclinician by end of the study), (3) number of telephone calls(total number of phone calls made to the clinician by end ofthe study), (4) total number of e-mails (total number of e-mails

Table 1. Characteristics of Recruiting Clinicians Stratified byRecruitment Rate

RecruitmentRate perMonth a

No. ofClinicians(%)

No. of EligibleParticipants perStrata (%)

No. of IneligibleParticipants perStrata (%)

0 32 (23.2) 0 (0) 8 (1.3)N0-0.5 44 (31.9) 112 (11.6) 69 (10.9)N0.5-1 27 (19.6) 162 (17.1) 235 (37.0)N1-2 20 (14.5) 197 (20.7) 158 (24.9)N2 15 (10.9) 480 (50.6) 164 (25.9)Total 138 (100) 951 (100) 634 (100)

a Recruitment rate: total number of participants recruited divided bythe number of months in the study.

Table 2. Clinician's Descriptive Data (n = 138)

VariablesMean ± SD orn (%)

Sex, male 73 (53)Age 42 ± 10Profession, physiotherapist 135 (98)Current position

Employee 67 (48.5)Business owner 71 (51.5)

Clinical experience (y) 19.5 ± 10Clinical experience managing LBP (y) 18.5 ± 9.5SES of suburb of clinician clinic (high) a 104 (75.5)Member of their respective association 103 (74.5)Training method (telephone) 79 (57.2)No. of letters b 1.1 ± 0.3No. of telephone call b 0.4 ± 0.3No. of e-mails b 0.3 ± 0.2


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Total no. of contacts (letter/e-mail/telephone call) b 1.8 ± 0.6No. of ineligible patients b 4.6 ± 13.9

LBP, low back pain; SES, socioeconomic status.a Suburb socioeconomic status—determined by comparing the clinic

postcode to Australia Bureau of Statistics data on economic advantage anddisadvantage.

b Number of contacts divided by the total time (months) participating

sent to the clinician by end of the study), (5) total number ofcontacts (total number of phone calls, letters, or e-mails madeand/or sent to the clinician by end of the study), and (6)number of ineligible patients referred (ineligible patients weredefined as patients not willing to participate or not fulfillingstudy inclusion criterion).

in the study.

Data AnalysisAnalyses were performed using STATA version 12

(College Station, TX).25 Descriptive statistics were per-formed to describe the clinician's characteristics and therecruitment rate for the study (defined as the number ofpatients per month). To evaluate factors that influencedclinicians' recruitment rate, a negative binomial regressionanalysis was conducted where recruitment rate was thedependent variable and the predictors described above(clinicians and operational characteristics) were independentvariables. We used the negative binomial regression analysisbecause the outcome data were overdispersed (tested bycomparing the variance of the data to the mean patient countrecruited by clinicianswith the likelihood ratio test). Variableswith significant univariate associations (P b .2) were enteredinto a backward stepwise multivariate regression model.Statistical significance was defined as P b .05. As cliniciansstarted the study on different dates, this was accounted for inthe analysis by including the number of days in the study as anoffset variable in the model. For continuous variables, theincident rate ratio (IRR) can be interpreted as the rate ratio inwhich the total number of participants is expected to changewith a 1-unit increase in the exposure variable. For binaryvariables, the IRR indicates the expected change in rate ofpatient recruitment when the variable is positive.

RESULTS

From 1147 clinicians initially contacted, 135 physiothera-pists (12.2%) and 3 chiropractors (7.7%) agreed toparticipate. Between October 2011 and November 2012,study clinicians screened 1585 patients. There were 951

eligible patients who entered the study (943 referred byphysiotherapists and 8 referred by chiropractors). Table 1shows participant recruitment rate per month. The overallrecruitment rate per clinician was 0.99 patients per month ofparticipation. A minority of study clinicians (n = 15 and allphysiotherapists) recruited more than 50% of the participants(n = 480). Thirty-two clinicians (23.2%) did not recruit asingle participant during the study period. The top 15clinicians (clinicians with recruitment rate N2 patients permonth) recruited a median of 24 participants to the study anddetermined that 164 patients were ineligible. For the lowrecruiters (clinicians with recruitment rate ≤2 patients permonth), the median was 3 and determined that 472 patientswere ineligible.

Clinician's descriptive data are presented in Table 2. Mostof the study clinicians were physiotherapists (98%) and had amean clinical experience managing LBP of 18.5 years. Morethan half of the clinicians preferred the training to be performedby telephone (57.2%) rather than face to face (42.8%).

Factors That Influenced Recruitment Rate: Univariate and MultivariateAnalyses

Five clinician factors (sex, age, clinical experience aspracticing clinician, clinical experience managing LBP, andwhether clinicians were members of their respective associa-tions) and 5 operational factors (training method, number ofletters, number of telephone calls, number of contacts—letter/e-mail/telephone call, and number of ineligible patientsreferred) revealed a significant association (P b .2) with

Table 3. Characteristics Associated With Recruitment oParticipants, Univariate and Multivariate Analysis (n = 138)

Factors

UnivariateAnalysis

MultivariateAnalysis

IRR (95% CI) IRR (95% CI)

Clinicians factorsSex, male 2.02 (1.23-3.31) a –Age 1.04 (1.01-1.06) a –Profession,physiotherapist

1.32 (0.80-2.18) –

Current position,employee c

0.49 (0.08-2.95) –

Clinical experience, y 1.03 (1.00-1.05) a –Clinical experiencemanaging LBP, y

1.03 (1.01-1.06) a –

SES of suburb ofclinician clinic, high d

1.13 (0.63-2.03) –

Member of theirrespective association

0.41 (0.24-0.72) a 0.42 (0.25-0.71) b

Operational factorsTraining method,telephone

2.98 (1.84-4.81) a 4.01 (2.38-6.79) b

No. of letters 0.95 (0.89-1.01) a –No. of telephone call 0.92 (0.82-1.03) a –No. of e-mails 0.94 (0.79-1.12) –Total no. of contacts,letter/e-mail/telephone call

0.97 (0.93-1.01) a –

No. of ineligible patients 1.04 (1.01-1.08) a 1.03 (1.02-1.06) b

With continuous variables, the IRR can be interpreted as the rate ratio in whichthe total number of participants is expected to change with a 1-unit increase inthe exposure variable. With binary variables, the IRR indicates the expectedchange in rate of patient recruitment when the variable is positive.CI, confidence interval; IRR, Incident rate ratio; LBP, low back pain.

a Candidate variables with significant univariate association (P b .2)that entered the multivariate analysis.

b P b .0001.c Employee compared with business owner.d Suburb socioeconomic status—determined by comparing the clinic

postcode to Australia Bureau of Statistics data on economic advantage anddisadvantage, defined as high, greater than or equal to AU $577, or lowless than AU $577.


189

f

,

patient recruitment in the univariate analyses (Table 3) andwere candidates for the multivariate analysis.

After the backward stepwise regression, 3 variables wereremaining in the model. These variables are presented inTable 3 with incident rate ratios. From the clinician'scharacteristics, only whether clinicians were members oftheir respective associations was associated (inversely) withrecruitment. Clinicians that were members of theirrespective associations had a recruitment rate less thanhalf that of nonmembers (P b .001). The other 2 variablesassociated with recruitment were operational factors(training method and number of ineligible patientsreferred). Clinicians that were trained over the telephonehad a recruitment rate 4.01 times greater than those trainedface to face. Similarly, clinicians that referred a highernumber of ineligible participants had a greater recruitmentrate, with incident rate ratio of 1.03 (P b .0001).

DISCUSSION

Main FindingsAlthough 41.3% of the clinicians referred 2 or less eligible

participants during the study period, we successfully recruitedour target sample (n = 951) in a reasonable period of time(13.8 months). The overall recruitment rate was 0.99 patients,per clinician, per month of participation. This providesevidence that, in relatively simple observational studies forLBP, where clinicians are reimbursed for their time, it shouldbe relatively easy to recruit large numbers of participants fromprimary care. The recruitment success of this study wasachieved mainly because 15 primary care clinicians recruited50.6% of the sample.

Among the clinician and operational characteristicsinvestigated, 3 of 14 factors increased recruitment. However,these factors must be considered carefully as they areunsurprising or uninterpretable and the practical implicationsseem limited. Clinicians that were members of theirrespective associations had a recruitment rate less thannonmembers conflicts with the view that members whoengage in continuing education are more likely to beinterested in research. Even in studies that recruit the requiredsample size in a reasonable time frame, identifying factorsthat increase recruitment seems challenging, providing astrong case for the urgent need for more studies.

This study investigated clinician and operational charac-teristics and did not assess the characteristics of patients;investigation would require a different study design, that is,one where the characteristics of patients not recruited to thetrial are also determined. Patients may decline participationfor a variety of reasons including lack of time, lack ofunderstanding of relevance of research question, alreadyanxious about their disease, and others. Understanding betterthe patient characteristics that predict participation in clinicaltrials of back pain is an important area for future research.

Comparison With Other StudiesAlmost universally, recruitment is a challenge.26 To date,

most of the studies investigating factors that influencerecruitment of patients in primary care have focused onRCTs.27 Although many of the challenges encountered withpatient recruitment to RCTs are also applicable to observationalstudies, there may be important differences.28 There is asignificant lack of research on observational study designs. Weidentified no previous observational studies that reportedrecruitment rates in primary care and, therefore, could notcompare our research findingswith previous studies in the field.

Findings fromour observational study show that clinicianstrained by telephone and those who refer ineligible patientsthroughout the study are likely to have higher recruitmentrates. Clinicians who are a member of their professionalassociation are less likely to recruit. These factors have notpreviously been identified in earlier studies as important to


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recruitment. The latest Cochrane review on strategies toinfluence recruitment for RCTs found that using telephonereminders, opt-out procedures requiring potential partici-pants to contact the trial team if they did not want to becontacted about a trial, making the trial open rather thanblinded, and mailing a questionnaire about home safety topotential participants to an injury prevention trial arefactors that improved recruitment in high-quality studies.5,7

A systematic review reported on a variety of strategies toimprove recruitment, the most common being the use ofletters, e-mails, and telephone calls to clinicians3,4; however,similar to our findings, these factors did not significantlyincrease recruitment.

Limitations and StrengthsSome of the strengths of this study are the large number

of clinicians that participated in this LBP study and thelarge number of patients recruited in a short period. Theselarge numbers have enabled us to robustly assess clinicianand operational features that, in combination, could leadto successful recruitment of patients to LBP studies inprimary care.

Oneweakness of this studywas that the factors investigatedmay apply predominantly to simple observational studies. Thesimplified design, minimal role required by the studyclinicians, and the reimbursement for the time and inconve-nience may have contributed to the rapid patient recruitment.The factors associated with recruitment were relativelyunexpected. Other clinician characteristics not investigated inthis study may be important in influencing recruitment.

Although previous studies have described financialreimbursement as important for recruiting clinicians andpatients,9,29 one of the few systematic reviews does notsupport this. Clinicians who identify reimbursement as a keyreason for participating in anRCT are nomore likely to recruitpatients than those who do not.20 In the current observationalstudy, financial reimbursement for both clinicians andparticipants may have influenced recruitment; however, wecould not assess this using our current methods. In addition,we could not assess if practice-level characteristics of theproviders affected recruitment. Factors such as full-time vspart-time employment status, ownership ofmultiple practices,employment of other therapists, specialty practices, number ofpatients treated per week, average duration of consultationsession, referral patterns, university affiliation, or otherorganizational factors were not measured in the currentstudy, and therefore, their effect on patient recruitmentremains unclear. Future research might explore the influenceof practice characteristics on research recruitment rates. Inaddition, we did not attend the clinics to observe if theproviders were completing participant recruitment as perprotocol, and this is a limitation of the study.

In this study, the money reimbursed for eligible and/orineligible patients was to cover clinicians' time spent in

recruiting participants, explaining the study to them, andliaising with the study staff and clerical and administrationcosts. The time involved in this process took from 30 to 45minutes, and the reimbursement valued the clinician's timeaccording to prevailing physiotherapy consultation fees. Thisstrategy was used to ensure that financial reimbursement wasnot considered an inducement to participate. To minimizeerrors, eligibility criteria were double checked by a studyresearcher at the time of the interview.

We advised at the initial training and re-enforcedthroughout the whole study period that all study cliniciansshould invite all consecutive patients presenting with LBP tothe study. If clinicians did not enroll consecutive patients, itwould have the potential to include sampling bias in the parentTRIGGERS study. However, we do not believe that thiswouldintroduce bias into this study of factors influencing recruitment.

In this study, clinicians were not randomly allocated toeither training by telephone or by face-to-face visit. Thetraining method was determined by the clinician, and thischoice may reflect other confounders in the practice.30

Clinicians that opted to be trained by telephone may havechosen this due to their busier clinic schedule suggestingcontact with a larger number of patients per day than otherclinicians and, hence, an increased opportunity to recruit.Regardless, the finding that, in a simple observational study,training of clinicians by telephone appears to be at least aseffective as face-to-face training for recruitment has impor-tant implications. The training administered by telephonewasdelivered one to one, as opposed to face-to-face trainingwhere 1 or more clinicians (up to 5) were trained at a giventime. The individualized training and feedback are effectivein improving recruitment.31 The results that better recruit-ment is associatedwith referral of more ineligible participantscould be due to a higher overall number of invitations. Therelationwith professionalmembership is a complete mystery.

The recruitment of primary care clinicians in this studywas based on an invitation letter sent bymail, and despite thisrelatively passive method of recruitment, we could interest asuitable number of clinicians in participating in our study in arelatively short while. Had we used more active methods ofencouraging clinicians to participate, such as providingeducational seminars and distributing advertisements andnewsletters to association databases, we may have had morerapid recruitment of clinicians. Chiropractors were identifiedby a Google search using the words “Chiropractor Sydney.”The order of appearance in the search may be affected by thesearch engine optimization, hence, favoring chiropractorswho have greater knowledge. However, it remains unclearwhether these clinicians would have recruited more subjectsto the study.

In this study, we contacted the Australian PhysiotherapyAssociation as our primary means of identifying physiothera-pists but used a Google search to identify chiropractors. Itwould have been better to use similar methods to identifyboth professions. Future studies should use similar methods


191

to recruit primary care clinicians. Either, physiotherapy andchiropractic associations should be contacted and using theGoogle engine to identify nonmember clinicians.

Practical Applications• This study provides evidence that, in relativelysimple observational studies for LBP, it should berelatively easy to recruit large numbers ofparticipants from primary care.

• However, even in studies that recruit the requiredsample size in a reasonable time frame, identifyingfactors that increase recruitment seems challeng-

Future ResearchThere is a small but emerging body of literature on factors

influencing recruitment. The operational factor (trained bytelephone) identified as influencing recruitment in this studymay only be appropriate in simple study designs but should beinvestigated further due to the potential to make clinicianrecruitment easier and cheaper. To date, there are no studiesinvestigating if primary care clinicians that are members oftheir respective associations are more or less likely toparticipate and recruit patients for research. This informationwould be of value, as clinicians that aremembersmay be easierto contact through their professional association. Future studiesshould also investigate if practice-level characteristics couldinfluence patient recruitment.

In addition, other potentially important factors that couldinfluence recruitment and/or clinicians' behavior, such asnumber of contacts madewith the clinician and reimbursementfor time involved for the clinician and administrative staff, needto be considered in future studies. A better understanding of thepatient characteristics associated with successful recruitment isalso urgently needed. Further research on factors that couldmaximize recruitment rate must be conducted. Factors thatinfluence patient recruitment in primary care are complex andremain unclear.
ing, providing a strong case for the urgent need for
more studies in this area.

CONCLUSIONS

Although patient recruitment is a challenge, this study ofrecruiting participants from primary care clinicians for a largeobservational study of LBP has been positive. Factorsidentified as influencing recruitment were professionalassociation (negative association), training by telephone, andreferring a higher number of ineligible participants.

This study has revealed factors associated with recruit-ment rate, although the ability to predict which clinician willrecruit based on operational and clinicians characteristicsseems restricted.

FUNDING SOURCES AND POTENTIAL CONFLICTS OF INTEREST

No funding sources or conflicts of interest were reportedfor this study.

CONTRIBUTORSHIP INFORMATION

Concept development (provided idea for the research):D.S., CM., M.F., M.H., L.P., C.W., J.L.Design (planned the methods to generate the results): DS.,C.M., M.F., M.H., L.P., C.W., J.L.

Supervision (provided oversight, responsible for orga-nization and implementation, writing of the manu-script): D.S., C.M., M.F, M.H, L.P, C.W, J.L.Data collection/processing (responsible for experi-ments, patient management, organization, or reportingdata): D.S., C.M., M.F., M.H., L.P., C.W., J.L.Analysis/interpretation (responsible for statistical anal-ysis, evaluation, and presentation of the results): D.S.,C.M., M.F., M.H., L.P., C.W., J.L.Literature search (performed the literature search): N.A.Writing (responsible for writing a substantive part of themanuscript): D.S., C.M., M.F., M.H., L.P., C.W., J.L.Critical review (revised manuscript for intellectual content,this does not relate to spelling and grammar checking):D.S.,C.M., M.F., M.H., L.P., C.W., J.L.

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Chapter Ten

Conclusions

193

10.1. Aim

The primary aim of this thesis was to contribute to a better understanding of the

mechanisms for low back pain. New knowledge was acquired in a number of ways that

included interviewing primary care clinicians, conducting relevant systematic reviews,

measuring exposure to back pain risk factors, and exploring prognosis for patients with

chronic low back pain.

The first study contributed knowledge on the mechanisms of onset of back pain, identifying

the short and long-term risk factors that primary care clinicians consider important in

triggering an episode of low back pain (Chapter Two). The studies described in Chapter

Four and Chapter Five continued this theme investigating a range of physical, psychosocial

(Chapter Four) and environmental factors (Chapter Five) that increase risk for an episode

of sudden onset, acute low back pain. The study presented in Chapter Six aimed to

systematically review whether magnetic resonance imaging findings of the lumbar spine

predict future low back pain. In terms of back pain management, the study presented in

Chapter Seven aimed to examine the prognosis and prognostic factors for patients with

chronic low back pain. The systematic review presented in Chapter Eight aimed to

investigate if the presence of magnetic resonance imaging findings identifies patients with

low back pain who respond better to particular interventions. Finally, the study presented in

Chapter Nine aimed to identify factors that influence recruitment of participants to a large

observational study.

10.2. Overview of principal findings

The observational study described in Chapter Two revealed that Australian primary

care clinicians believe that biomechanical risk factors (89.3%), such as lifting (17.5%),

prolonged sitting (9.1%) and physical trauma (8.9%), are the most likely short-term risk

factors for low back pain. Biomechanical risk factors (54.2%), such as prolonged sitting

(13.4%) and lifting (10.9%), and individual risk factors (39%), such as physical inactivity

(9.1%) and other individual risk factors (5.8%) are the most endorsed long-term risk factors.

Surprisingly, commonly reported risk factors, such as psychological or psychosocial factors

(0.6% and 3.1% for short and long-term respectively), and genetic risk factors (0.0% and

0.2% for short and long-term respectively) were considered unimportant by clinicians.

194

Prior to this thesis there had been no high quality study that used a case-crossover

design to determine the effects of physical, psychosocial and meteorological factors on the

risk of an episode of sudden onset, acute back pain. The case-crossover study described in

Chapter Four demonstrated for the first time that brief exposure to a range of physical

factors (e.g. manual tasks involving awkward postures, or manual tasks involving an object

that could not be positioned close to the body) and psychosocial factors (being distracted

during a task or being fatigued) can considerably increase the risk of an episode of low back

pain. However, these associations were not moderated by habitual physical activity, BMI,

previous episodes of low back pain, depression or anxiety. Age moderated the risk associated

with exposure to heavy loads and sexual activity. Chapter Five presents a case-crossover

study investigating the influence of weather conditions on risk of low back pain. The findings

demonstrated that there was no association between temperature, relative humidity, air

pressure, wind direction and precipitation and risk of back pain. Higher wind speeds slightly

increased the odds of back pain onset, although the effect was not considered clinically

important.

The systematic review investigating magnetic resonance imaging (MRI) findings as a

predictor of future low back pain (Chapter Six) identified twelve longitudinal studies. Of

these, most enrolled small samples, investigated different MRI findings and presented varied

clinical outcomes. Across the 46 MRI findings investigated, no consistent associations with

clinical outcomes were identified. Three different studies reported associations for Modic

changes with pain, disc degeneration with disability in samples with current low back pain

and disc degeneration with pain in a mixed sample of patients with and without current low

back pain.

The prognosis study described in Chapter Seven revealed that patients with chronic

low back pain presenting to a private, community-based group exercise program improved

clinical outcomes significantly, with greater improvements in disability compared to pain at

12 months. The predictors investigated accounted for only 10% and 15% of pain and

disability outcomes, respectively, suggesting that there is much to learn about the factors

influencing recovery in this group of patients.

Chapter Eight reports the findings from a systematic review investigating if the

presence of magnetic resonance imaging findings identifies patients with low back pain who

respond better to particular interventions. Although this review identified eight clinical trials,

195

investigating 38 interactions for low back pain and sciatica, only two individual trials

suggested some magnetic resonance imaging findings that might be effect modifiers for

specific interventions. It is unknown if these subgroup interactions accurately represent the

association, given the limited number of suitable trials and the heterogeneity across them.

The observational study described in Chapter Nine found three variables (clinicians

not members of their professional association, clinicians trained by phone and clinicians who

referred a larger number of ineligible patients) associated with the rate at which primary care

clinicians recruited patients to the study. However, the applicability and understanding of

some of these factors seems counterintuitive; indicating that identifying primary care

clinicians likely to recruit at faster rates is complex.

The findings of these studies have advanced the understanding of mechanism of low

back pain in relation to risk, prognosis and response to treatment. There are several important

implications and directions for future research that arise from these studies.

10.3. Implications and suggestions for future research

10.3.1. Mechanism: Risk factors for low back pain

Currently, there are a number of recognised risk factors for low back pain

(HOOGENDOORN et al., 2000; LINTON, 2001; HAMBERG-VAN REENEN et al., 2007;

HENEWEER et al., 2011; LANG et al., 2012), however, most of these risk factors are based

on long term exposure (e.g. smoking), and many are not modifiable (e.g. age). The

identification of risk factors in primary care is crucial to help the development of new

research, which may lead to future prevention programs (RUBIN, 2007). The study presented

in Chapter Two, based on primary care clinicians views, identified important short

(biomechanical) and long-term (biomechanical and individual) risk factors for low back pain.

While primary care clinicians beliefs on biomechanical and individual risk factors are aligned

with past research (TAYLOR et al., 2014), the lack of consideration towards psychosocial

and genetic risk factors is quiet surprising. Thus, the reasons why primary care clinicians

consider psychosocial and genetic risk factors unimportant need to be further investigated to

aid management and prevention of this condition. Previous studies suggest that psychosocial

risk factors (e.g. low job control) are often correlated with biomechanical risk factors (e.g.

intensive load) (MACDONALD et al., 2001). One reason why experienced clinicians think

196

these factors are not important, may be that they have limited expertise in assessing these

factors as triggers for low back pain. Another reason may be that this population represents a

general sample of the population, while previous studies have focused on occupational

settings (HOOGENDOORN, VAN POPPEL et al., 2000; KERR et al., 2001; HOY et al.,

2010). Although low back pain is commonly reported as multifactorial (TAYLOR, GOODE

et al., 2014), future studies are needed to investigate if two or more factors present higher risk

of back pain development.

The large case-crossover study presented in Chapter Four provides clear evidence

that brief exposure to a range of physical and psychosocial triggers substantially increased

risk for a new episode of back pain. One of the advantages of this study is the novel design

used and that the risk factors found to increase the risk of a low back pain episode are readily

modifiable. In this robust design, participants act as their own controls, and therefore the

perfect matching of cases and controls eliminates potential effects of unmeasured

confounders, such as genetic and lifestyle influences, on back pain development

(HOOGENDOORN, VAN POPPEL et al., 2000; HENEWEER, STAES et al., 2011). The

fact that the risk factors found in this study are modifiable (e.g. lifting) will support the

development of new prevention approaches for back pain. Previous research has focused on

factors that are not modifiable (e.g. age and height) or involve long-term exposure (e.g.

smoking) (KOPEC, SAYRE and ESDAILE, 2004; SHIRI et al., 2010). While we found a

strong association with most of factors investigated, future studies are needed to validate

these factors in other populations. Additionally, there may be other potential risk factors we

failed to measure that may be modifiable.

Well-designed studies controlling exposure to these risk factors, either at home or in

the workplace, should be a priority as secondary prevention of low back pain could reduce

individuals’ suffering and reduce heath expenditure. Also, future studies could evaluate the

effect of educating patients with previous history of back pain, providing accurate

information about the natural history of the condition to help reduce patient’s concerns and to

promote compliance with prevention strategies. The results of this study will also have

significant implications for clinicians and policy makers for the control of low back pain

episode.

The results of the case-crossover study presented in Chapter Five showed no

association between temperature, relative humidity, air pressure, wind direction, precipitation

197

and sudden onset, acute low back pain. Higher wind speed and wind gust speed, only slightly

increase the risk of back pain and, while this reached statistical significance, the magnitude of

the increase was not considered clinically important. Interestingly, this is the first study to use

a robust case-crossover design to investigate the influence of the weather on back pain.

Future research could focus on a wide range of patients’ characteristics (e.g. beliefs, mood,

memory) to explain individual differences in weather sensitivity. Future research should

determine if this insignificant association of weather parameters with back pain found in

Sydney, Australia, holds in more extreme climate conditions and in different clinical settings.

At the present, it seems that other risk factors are more important for the development of

acute back pain, such the factors investigated in Chapter Four (physical and psychosocial).

Lumbar imaging is routinely prescribed for the diagnosis of patients with low back

pain (JENSEN et al., 2008), however, the importance of the findings remains controversial

(MODIC and ROSS, 2007). Previous studies revealed high rates of abnormalities on MRI in

people without low back pain (JARVIK et al., 2001), though, this may represent markers of

early pre-symptomatic disease that is later characterized by episodes of back pain. Chapter

Six reported the results from a systematic review on the association of magnetic resonance

imaging and future low back pain. Although this review found that three single studies

presented significant associations (Modic changes with pain and disc degeneration with

disability, in samples with current low back pain; and disc degeneration with pain in a mixed

sample), it is uncertain if these estimates accurately represent the association given the

quality, sample size and heterogeneity among the included studies. Thus, further large, high-

quality studies that address the aforementioned problems are clearly needed to help determine

the clinical meaningfulness of lumbar imaging in relation to low back pain.

Investigations into the association between lumbar MRI findings and low back pain

are complicated as multiple findings are present at the same time. Findings such as lumbar

intervertebral disc protrusions or endplate changes, almost always co-exist with other

degenerative disc findings, such as disc height reduction and signal intensity (WANG,

VIDEMAN and BATTIE, 2012). An initial strategy to advance this area of investigation

would be to recognise which MRI findings typically occur together and whether clusters of

findings are more predictive of outcome than single findings.

198

10.3.2. Management: Prognosis and subgroups for low back pain

Understanding prognostic factors that are associated with better or worse disease

outcome can help identify possible determinants and causal pathways for low back pain,

which may lead to more effective management strategies (HAYDEN et al., 2010). The

findings of the prognosis study reported in Chapter Seven showed that patients with chronic

low back pain who presented to an exercise program incorporating cognitive behaviour

therapy improved considerably over the course of one year. However, the predictors

investigated accounted for only 10% and 15% of pain and disability outcomes, respectively.

This information on prognostic outcome is important for patients and clinicians as it helps to

set realistic expectations and can be used to guide decision making regarding the need for

additional interventions. It is likely that prognosis depends on multiple factors (HAYDEN et

al., 2009). Further investigation of important and novel predictors are needed (e.g. stress, job

satisfaction, beliefs). Advanced phases of investigation are needed to progress the low back

pain prognosis field, including confirmation studies for prognostic factors with more frequent

(e.g. monthly) and longer follow-up (e.g. longer than 12 months).

Selecting a representative cohort is a key consideration in designing studies on the

prognosis of back pain. For studies investigating the prognosis of low back pain, the ideal is

to assemble a sample that is at risk of developing chronic low back pain and then identifying

an inception cohort from incident cases (COSTA LDA et al., 2007). These inception cohorts

generally provide stronger evidence on prognosis than cohorts assembled from available

cases (e.g. survival cohorts) and are therefore recommended for future research. Lastly,

intervention strategies for low back pain should make greater use of prognostic data to

support the theoretical rationale for interventions and to identify the group of patients most

likely to benefit from it.

The effects of most clinical interventions for the management of low back pain

reported in trials are usually classified as small or moderate at best (HAYDEN et al., 2005).

There is always the argument that different patients will not respond similarly to the same

intervention and, therefore, subgroups should be considered (COSTA LDA et al., 2013). The

systematic review in Chapter Eight found eight trials that investigated 38 subgroup

interactions; one presented a significant effect modifier for low back pain and one for sciatica

populations. Although some statistically significant subgroup interactions were noted, it is

questionable if the estimates accurately represent the effect modification. This is largely due

199

to the limited number, heterogeneity and overall quality of studies found. Interestingly,

subgroup studies are a research priority in the low back pain field since 2007 (HENSCHKE

et al., 2007; COSTA LDA, KOES et al., 2013), however, there are only a few clinical trials

and most are underpowered. Therefore, well-designed, adequately powered trials are

required. Moreover, the general content and reporting of subgroup analyses is rather poor. It

is thus recommended, that authors use available guidelines when performing subgroup

analyses to ensure that they are reliable and of a good standard (ROTHWELL, 2005).

Another problem with subgroup analysis is that the sample size required is around

four times larger than if the only interest was the main effect of treatment (CUZICK, 1999).

Therefore, acquiring a reasonable sample size is always a challenge for subgroup studies. The

combination of data across multiple studies may be a practical option to gain power and

overcome some of the concerns reported in our review. However, data should be combined

only when studies are homogeneous. This is not always obvious and requires great caution.

10.3.3. Factors influencing recruitment rate

Identifying important factors that influence recruitment to observational studies is

required to improve the efficiency, impact and success of research studies (WILLIAMS et al.,

2014). Many of the factors investigated in Chapter Nine did not appear to influence

participant recruitment rate. The identification of factors that increase recruitment remains

challenging, providing a strong case for the urgent need for more studies in this area. For this

reason, future research should appropriately focus on identifying other variables that could be

incorporated with factors already known to improve participant recruitment rate.

Recruiting participants to research studies in primary care setting presents some

unique challenges as primary care studies often rely on clinicians to screen and enrol patients.

One possible way to optimise recruitment of patients to observational studies is the use of a

computerised pop-up prompts. Previous studies have reported that one of the main problems

in recruiting patients was that clinicians are time poor and normally forget about the study

due to the large amount of patients seen per day (SPAAR et al., 2009). This new method

reminds clinicians of potential eligible patients using computer prompts when patients’

information is entered into their electronic medical records. This approach could potentially

enhance recruitment to future research studies.

200

Finally, the series of studies described in this thesis provide new, important

information that lead to a better understanding of the mechanisms of low back pain. It is

hoped that the findings and recommendations that arise from this thesis are widely adopted in

future low back pain research.

201

10.4. References

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J. H. MCAULEY, A. DAS and L. O. COSTA, Prognosis of chronic low back pain: design of

an inception cohort study. BMC Musculoskelet Disord, 8, p. 11, 2007.

COSTA LDA, C., B. W. KOES, G. PRANSKY, J. BORKAN, C. G. MAHER and R. J.

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CUZICK, J., Interaction, subgroup analysis and sample size. IARC Sci Publ, 148, p. 109-

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HAMBERG-VAN REENEN, H. H., G. A. ARIENS, B. M. BLATTER, W. VAN

MECHELEN and P. M. BONGERS, A systematic review of the relation between physical

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HAYDEN, J. A., M. W. VAN TULDER, A. MALMIVAARA and B. W. KOES, Exercise

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APPENDIX

205

Appendix A: Media coverage of Chapter Five

Television:

1. Channel 9 News: http://buff.ly/U5R25m

2. ABC News:

Broadcasts:

1. 2UE

2. 2UE 954 News Talk

3. 6PR Perth

4. 4BC Brisbane

Online:

1. Wiley: http://au.wiley.com/WileyCDA/PressRelease/pressReleaseId-111044.html

2. News.com.au: http://www.news.com.au/national/breaking-news/back-pain-dont-blame-it-

on-the-rain/story-e6frfku9-1226984395748

3. Life hacker Australia: http://www.lifehacker.com.au/2014/07/why-your-back-pain-has-

nothing-to-do-with-the-weather/

4. Business insider Australia: http://www.businessinsider.com.au/low-back-pain-dont-blame-

the-weather-2014-7

5. The Washington Post: http://www.washingtonpost.com/news/to-your-

health/wp/2014/07/10/no-uncle-fred-the-weather-has-nothing-to-do-with-your-back-pain/

206

6. Channel 9 News: http://news.ninemsn.com.au/health/2014/07/10/14/08/back-pain-don-t-

blame-it-on-the-rain

7. Live Science: http://www.livescience.com/46740-back-pain-not-linked-weather.html

8. Vancouver Desi: http://www.vancouverdesi.com/lifestyle/dont-curse-weather-for-low-

back-pain/768630/

9. News Medical: http://www.news-medical.net/news/20140710/Acute-episodes-of-low-

back-pain-not-linked-to-weather-conditions.aspx

10. Northern Voices Online: http://nvonews.com/dont-curse-weather-for-low-back-pain/

11.TVNZ One News: http://tvnz.co.nz/world-news/back-pain-don-t-blame-rain-6024295

12. Science Codex: http://www.sciencecodex.com/low_back_pain_dont_blame_the_weather-

137261

13. Medical Daily: http://www.medicaldaily.com/lower-back-pain-not-made-worse-

inclement-weather-such-humidity-or-cold-292130

14. E Newspaper of India: http://www.eni.network24.co/lifestyle/dont-curse-weather-for-

low-back-pain-12574_13

15. EurekAletr: http://www.eurekalert.org/pub_releases/2014-07/w-lbp070814.php

16.MedicalXpress: http://medicalxpress.com/news/2014-07-pain-dont-blame-weather.html

17. Daily Mail: http://www.dailymail.co.uk/wires/aap/article-2687005/Back-pain-dont-

blame-rain.html

18. Yahoo News: http://news.yahoo.com/feel-bones-back-pain-not-linked-weather-

071628526.html

207

19. The Australian: http://www.theaustralian.com.au/news/latest-news/back-pain-dont-

blame-it-on-the-rain/story-fn3dxiwe-

1226984395748?nk=179f05082c5bbe67589cada8dbfdbe1d

20. TechieTonics: http://www.techietonics.com/health-tonics/back-pain-does-not-link-to-the-

weather-conditions-posture-is-to-be-blamed.html

21. Apple Balla: http://www.appleballa.com/2014/07/154959/dont-curse-weather-low-back-

pain

22. Nature World News: http://www.natureworldnews.com/articles/7988/20140710/lower-

back-pain-related-weather-study.htm

23. Web MD: http://www.webmd.boots.com/back-pain/news/20140710/weather-lower-back-

pain

24. Daijiworld.com: http://www.daijiworld.com/news/news_disp.asp?n_id=247590

25. Science World Report:

http://www.scienceworldreport.com/articles/15929/20140710/low-back-pain-not-linked-to-

weather-conditions.htm

26. Health Medicine Network: http://healthmedicinet.com/i/low-back-pain-dont-blame-the-

weather/

27. Business Standard: http://www.business-standard.com/article/news-ians/don-t-curse-

weather-for-low-back-pain-114071000586_1.html

28. Best Health: http://besthealth.bmj.com/x/news/758164/news-

item.html?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+bestheal

th%2Fnews+(Best+Health%3A+Latest+news)

208

29. Topix: http://www.topix.com/forum/health/back-pain/TTCM5SSIBICJR3OTE

30. The times of India: http://timesofindia.indiatimes.com/life-style/health-

fitness/health/Dont-curse-weather-for-low-back-pain/articleshow/38136126.cms

31. University Herald: http://www.universityherald.com/articles/10332/20140710/lower-

back-pain-weather-conditions-sydney-australia.htm

32. Huffington Post US: http://www.huffingtonpost.com/2014/07/10/weather-low-back-

pain_n_5573968.html

33. National Pain Report: http://americannewsreport.com/nationalpainreport/researchers-say-

weather-not-linked-to-back-pain-8824219.html

34. Daily RX: http://www.dailyrx.com/low-back-pain-onset-not-tied-weather-factors-

humidity-and-temperature

35. Upstart Magazine: http://www.upstartmagazine.com/weather-doesnt-impact-lower-back-

pain-says-study/295012/

36. NVO News: http://nvonews.com/weather-doesnt-cause-lower-back-pain/

37. Daily Mail Australia: http://www.dailymail.co.uk/health/article-2687631/Dont-listen-

granny-weather-NO-impact-state-bad-back.html

38. KSBY 6: http://www.ksby.com/news/study-finds-weather-does-not-affect-back-pain/

39. Bayou Buzz: http://www.bayoubuzz.com/healthcare/healthcare-news/item/702916-

medical-news-today-back-pain-not-brought-on-by-weather-except-for-trivial-wind-effect

40. KYTX 19: http://www.cbs19.tv/story/25984211/health-alert-back-and-neck-pain-not-

linked-to-weather

209

41. My Foxny: http://www.myfoxny.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

42. 13 ABC: http://www.13abc.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

43. Daily Digest News: http://dailydigestnews.com/2014/07/researchers-stop-blaming-the-

weather-for-your-lower-back-pain/

44. The Daily Express: http://www.express.co.uk/life-style/health/487969/Research-shows-

no-link-between-cold-weather-and-back-pain

45. Philly.com:

http://www.philly.com/philly/health/HealthDay689584_20140710_Don_t_Blame_Bad_Weat

he for_Your_Aching_Back.html

46. Fox News: http://www.foxnews.com/health/2014/07/10/feel-it-in-your-bones-back-pain-

not-linked-with-weather/

47. Design & Trend: http://www.designntrend.com/articles/16542/20140710/weather-does-

not-affect-lower-back-pain-latest-study-suggests.htm

48. Headlines & Global News: http://www.hngn.com/articles/35733/20140710/weather-

conditions-increase-low-back-pain-study.htm

49. Counsel & Heal: http://www.counselheal.com/articles/10419/20140710/weather-patterns-

not-tied-to-back-pain.htm

50. CBS Atlanta: http://atlanta.cbslocal.com/2014/07/10/study-low-back-pain-not-linked-to-

weather/

51. TIME: http://time.com/2970789/achy-back-dont-blame-the-weather/

210

52. Science Recorder: http://www.sciencerecorder.com/news/lower-back-pain-dont-blame-

the-weather/

53. Medical News Today: http://www.medicalnewstoday.com/articles/279435.php

54. Los Angeles Times: http://www.latimes.com/science/sciencenow/la-sci-sn-back-pain-

bad-weather-20140710-story.html

55. Red Orbit: http://www.redorbit.com/news/health/1113188840/low-back-pain-not-caused-

by-the-weather-071014/

56. Tech Times: http://www.techtimes.com/articles/10146/20140710/achy-back-due-bad-

weather.htm

57. IndiLeak: http://www.indileak.com/dont-curse-weather-for-low-back-pain/

58. Nelms Pharmacy: https://nelmspharmacy.com/article.php?id=689584

59. Health Magazine: http://news.health.com/2014/07/10/dont-blame-bad-weather-for-your-

aching-back/

60. Science Daily: http://www.sciencedaily.com/releases/2014/07/140710081200.htm

61. Arthritis Research UK: http://www.arthritisresearchuk.org/news/general-

news/2014/july/weather-conditions-do-not-affect-low-back-pain.aspx

62. Mental Help:

http://www.mentalhelp.net/poc/view_doc.php?type=news&id=165586&cn=72

63. Smile-on News: http://www.smile-onnews.com/news/view/weather-not-to-blame-for-

low-back-pain

64. India Today: http://indiatoday.intoday.in/story/low-back-pain-monsoon/1/370700.html

211

65. CVBT: http://www.centralvalleybusinesstimes.com/stories/001/?ID=26265

66. Kuam News: http://www.kuam.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

67. People Say About: http://peoplesayabout.com/dont-blame-bad-weather-for-your-aching-

back/

68. News Hub:

http://au.newshub.org/feel_it_in_your_bones_back_pain_not_linked_with_weather_1926696.

html

69. News 10 ABC: http://www.news10.com/story/25985267/dont-blame-bad-weather-for-

your-aching-back

70. NEWS 724 : http://news724.com/feel-it-in-your-bones-back-pain-not-linked-with-

weather/

71. WTVM 9: http://www.wtvm.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

72. Immunology: http://immunologynews.blogspot.com.au/2014/07/lower-back-pain-not-

triggered-by.html

73. Economy Lead: http://www.economylead.com/lifestyle/back-pain-linked-weather-22667

74. Isupon: http://isupon.com/dont-curse-weather-for-low-back-pain/

75. Celebrities Snitch: http://celebritiessnitch.com/bad-back-dont-blame-the-rain-research-

shows-no-link-between-cold-weather-and-back-pain/

76. VEOOZ: http://www.veooz.com/news/wHJyc4h.html

212

77. 6 Minutes: http://www.6minutes.com.au/news/latest-news/weather-link-to-back-pain-a-

lot-of-hot-air

78. RTT NEWS: http://www.6minutes.com.au/news/latest-news/weather-link-to-back-pain-a-

lot-of-hot-air

79. News Ledge: http://www.newsledge.com/back-pain-blues-study-refutes-weather-link-

7672

80. Health Central:

http://www.healthcentral.com/dailydose/cf/2014/07/10/study_finds_lower_back_pain_not_tie

d_to_weather

81. Betty Hardwick Center:

http://www.bhcmhmr.org/poc/view_doc.php?type=news&id=165586&cn=72

82. Regular News Update: http://regularnewsupdate.com/?p=48887

83. 6 WLNS: http://www.wlns.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

84. Delhi Daily News: http://www.delhidailynews.com/news/Weather-does-not-cause-back-

pain-1405011439/

85. Biocompare: http://www.biocompare.com/Life-Science-News/165005-Low-Back-Pain-

Don-t-Blame-The-Weather/

86. Breaking News: http://palashbd.com/tag/says-study/

87. Fox 23: http://www.myfoxmaine.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

213

88. Chicago Tribune: http://www.chicagotribune.com/health/la-sci-sn-back-pain-bad-

weather-20140710,0,4484041.story

89. Silo Breaker: http://news.silobreaker.com/bad-weather-is-not-affecting-your-back-pain--

but-high-winds-might-5_2268078554707132465

90. Khaleej Times: http://www.khaleejtimes.com/kt-article-display-

1.asp?section=health&xfile=/data/health/2014/July/health_July10.xml

91. Rheumatology: http://www.rheumatologyupdate.com.au/latest-news/weather-link-to-

back-pain-a-lot-of-hot-air

92. Z News: http://zeenews.india.com/news/health/fitness/don-t-curse-weather-for-low-back-

pain_28709.html

93. Ethiopia News Hub:

http://et.newshub.org/don_t_curse_weather_for_low_back_pain_1938312.html

94. Science News Line: http://www.sciencenewsline.com/summary/2014071011150015.html

95. Health Living: http://healthylng.blogspot.com.au/2014/07/don-blame-bad-weather-for-

your-aching.html

96. Health Day – News for Healthier living: http://consumer.healthday.com/bone-and-joint-

information-4/backache-news-53/don-t-blame-bad-weather-for-your-aching-back-

689584.html

97. News Max – Health: http://www.newsmaxhealth.com/Health-News/backache-pain-

symptoms-weather/2014/07/10/id/581893/

98. NBC News: http://www.nbcnews.com/id/55615058

214

99. The Advertiser – Adelaide: http://www.adelaidenow.com.au/news/breaking-news/back-

pain-dont-blame-it-on-the-rain/story-fni6ul2m-

1226984395748?nk=f1339b0422d39b4ed34178ee98d4198a

100. Deccan Herald: http://www.deccanherald.com/content/418918/dont-curse-weather-low-

back.html

101. Fox 5 – Las Vegas: http://www.fox5vegas.com/story/25985267/dont-blame-bad-

weather-for-your-aching-back

102. Yotta Fire: http://yottafire.com/2014/07/does-weather-affect-back-pain-no-new-study-

finds/

103. ANI News: http://www.aninews.in/newsdetail9/story175283/weather-doesn-039-t-

cause-low-back-pain-say-scientists.html

104. The Morung Express: http://www.morungexpress.com/health/118511.html

105. The Free Press Journal: http://freepressjournal.in/dont-curse-weather-for-low-back-pain/

106. The University of Sydney:

http://sydney.edu.au/news/84.html?newscategoryid=1&newsstoryid=13764

107. 12 WBoy: http://www.wboy.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

108. Perth Now: http://www.perthnow.com.au/news/breaking-news/back-pain-dont-blame-it-

on-the-rain/story-fnhrvfuw-1226984395748?nk=f1339b0422d39b4ed34178ee98d4198a

109. Herald Sun Melbourne: http://www.heraldsun.com.au/news/breaking-news/back-pain-

dont-blame-it-on-the-rain/story-fni0xqi4-

1226984395748?nk=0f0749c3e80365b2b3cc4dc0e5f26705

215

110. Medicine Net: http://www.medicinenet.com/script/main/art.asp?articlekey=179416

111. Bright Surf:

http://www.brightsurf.com/news/headlines/98424/Low_back_pain_Dont_blame_the_weather

.html

112. New Kerala: http://www.24dunia.com/english-news/shownews/8/Don-t-curse-weather-

for-low-back-pain/19150408.html

113. Armenian Medical Network: http://www.health.am/ab/more/low-back-pain-dont-blame/

114. Eye Witness News: http://www.wfsb.com/story/25985267/dont-blame-bad-weather-for-

your-aching-back

115. Womens Health:

http://www.womenshealth.gov/news/healthday/en/2014/jul/10/689584.html

116. The Siasat Daily: http://www.siasat.com/english/news/dont-curse-weather-low-back-

pain

117. ABC News 4: http://www.abcnews4.com/story/25985267/dont-blame-bad-weather-for-

your-aching-back

118. KHQ: http://www.khq.com/story/25985267/dont-blame-bad-weather-for-your-aching-

back

119. InteliHealth: http://www.intelihealth.com/news/dont-blame-bad-weather-for-your-

aching-back?level=0

120. KMPH Fox 26: http://www.kmph.com/story/25985267/dont-blame-bad-weather-for-

your-aching-back

216

121. MedBroadcast:

http://www.medbroadcast.com/health_news_details.asp?news_id=31673&news_src=1&news

_channel_id=1007#.U7-TsvmSx8E

122. My Fox Houston: http://www.myfoxhouston.com/story/25985267/dont-blame-bad-


123. Mangalorean:

http://www.mangalorean.com/news.php?newstype=local&newsid=494792

124. The Daily Telegraph: http://www.dailytelegraph.com.au/news/breaking-news/back-pain-

dont-blame-it-on-the-rain/story-fni0xqi3-


125. Geelong Advertiser: http://www.geelongadvertiser.com.au/news/national/back-pain-

dont-blame-it-on-the-rain/story-fnjbnvyf-1226984395748

126. Spire Healthcare: http://www.spirehealthcare.com/patient-information/health-

news/orthopaedic-surgery/801734511-low-back-pain-cannot-be-linked-to-weather-

conditions-/

127. Health Canal: http://www.healthcanal.com/disorders-conditions/pain/52954-low-back-

pain-don-t-blame-the-weather.html

128. Wonder woman: http://wonderwoman.intoday.in/story/low-back-pain-

monsoon/1/111692.html

129. Terra Daily:

http://www.terradaily.com/reports/Low_back_pain_Dont_blame_the_weather_999.html

217

130. Fox 42: http://www.fox42kptm.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

131. Fox 2127: http://www.fox2127.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

132. People’s Media: http://peoplesmedia24.com/dont-blame-bad-weather-for-your-aching-

back/

133. The George Institute: http://www.georgeinstitute.org.au/media-releases/rain-and-back-

pain-not-

linked?utm_content=buffer4669e&utm_medium=social&utm_source=facebook.com&utm_c

ampaign=buffer

134. Harvard Medical School: http://www.health.harvard.edu/blog/bad-weather-isnt-blame-

aching-back-201407117262

135. Guelph Mercury: http://www.guelphmercury.com/living-story/4627655-study-finds-no-

link-between-weather-and-lower-back-pain/

136. TV 3: http://www.tv3.ie/entertainment_article.php?locID=1.803.1098&article=139873

137. Montlhly Prescribing Reference: http://www.empr.com/back-pain-dont-blame-the-

weather/article/360458/

138. Health Professionals Network: http://www.hcplive.com/articles/Weather-Conditions-

Not-Associated-With-Lower-Back-Pain

139. Doctors Lounge: http://www.doctorslounge.com/index.php/news/pb/48085

140. The Record: http://www.therecord.com/living-story/4627655-study-finds-no-link-

between-weather-and-lower-back-pain/

218

141. The Baltimore Sun: http://www.baltimoresun.com/health/la-sci-sn-back-pain-bad-

weather-20140710,0,2527158.story

142. 8 News Now: http://www.8newsnow.com/story/25985267/dont-blame-bad-weather-for-

your-aching-

back?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+lasvegasnow

%2Fhealth+(8NewsNOW.com+-+Health+News)

143. Start at 60: http://www.startsatsixty.com.au/health/stop-blaming-it-on-the-weather

144. Your News Now: http://www.hometownstations.com/story/25985267/dont-blame-bad-


145. WMBB Northwest Florida: http://www.wmbb.com/story/25985267/dont-blame-bad-


146. GTN News: http://www.mygtn.tv/story/25985267/dont-blame-bad-weather-for-your-

aching-back

147. Central Coast News: http://health.keyt.com/story/25985267/dont-blame-bad-weather-

for-your-aching-back

148. Health e Galaxy: http://www.hegalaxy.com/weather-conditions-not-associated-with-

low-back-pain/

149. The Hamilton Spectator: http://www.thespec.com/living-story/4627655-study-finds-no-

link-between-weather-and-lower-back-pain/

150. Australian News:

http://www.australiannews.net/index.php/sid/223696183/scat/88f7d0d02bea1b33/ht/Weather-

doesnt-cause-low-back-pain-say-scientists

219

151. 7 News Denver: http://www.thedenverchannel.com/news/study-finds-no-link-between-

certain-weather-conditions-lower-back-pain

152. Record Search Light: http://www.redding.com/news/national/study-finds-no-link-

between-certain-weather-conditions-lower-back-pain

153. Health News Digest: http://www.healthnewsdigest.com/news/weather0/Low-Back-Pain-

Don-t-Blame-the-Weather_printer.shtml

154. WBKO: http://wn.wbko.com/story/25985267/dont-blame-bad-weather-for-your-aching-

back

155. NBC 40: http://www.nbc40.net/story/25985267/dont-blame-bad-weather-for-your-

aching-back

156. 760 KFMB: http://www.760kfmb.com/story/25985267/dont-blame-bad-weather-for-

your-aching-back

157. Action 3 News: http://health.kmtv.com/story/25985267/dont-blame-bad-weather-for-

your-aching-back

158. Bio-Medicine: http://www.bio-medicine.org/medicine-news-1/Low-back-pain-3F-Dont-

blame-the-weather-127490-1/

159. Israel Foreign Affairs News: http://israelforeignaffairs.com/dont-attribute-inclemency-

for-the-aching-back/

160. Live 5 News: http://www.live5news.com/story/25985267/dont-blame-bad-weather-for-

your-aching-back

161. Tulsa’s Channel: http://www.ktul.com/story/25985267/dont-blame-bad-weather-for-

your-aching-back

220

162. Walb News: http://www.walb.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

163. Kusi News: http://www.kusi.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

164. Drugs.com: http://www.drugs.com/news/don-t-blame-bad-weather-your-aching-back-

52308.html

165. Medline Plus: http://www.nlm.nih.gov/medlineplus/news/fullstory_147239.html

166. Wrex: http://www.wrex.com/story/25985267/dont-blame-bad-weather-for-your-aching-

back

167. Yahoo Health: http://health.yahoo.net/news/s/hsn/don-t-blame-bad-weather-for-your-

aching-back

168. Healthy Living: http://healthyliving.msn.com/diseases/back-pain/dont-blame-bad-


169. Weekly Times Now: http://www.weeklytimesnow.com.au/news/national/back-pain-

dont-blame-it-on-the-rain/story-fnjbnvyg-1226984395748

170. NBC Right Now: http://www.nbcrightnow.com/story/25985267/dont-blame-bad-


171. News Net 5: http://www.newsnet5.com/news/national/study-finds-no-link-between-


172. WAFB: http://www.wafb.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

221

173. KSFY: http://www.ksfy.com/story/25985267/dont-blame-bad-weather-for-your-aching-

back

174. WAFF: http://www.waff.com/story/25985267/dont-blame-bad-weather-for-your-aching-

back

175. The Courier Mail Brisbane: http://www.couriermail.com.au/news/breaking-news/back-

pain-dont-blame-it-on-the-rain/story-fnihsfrf-


176. Black Christian News: http://www.blackchristiannews.com/2014/07/if-you-have-pain-

in-your-lower-back-dont-blame-the-weather/

177. KSLA News: http://www.ksla.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

178. News West 9: http://www.newswest9.com/story/25985267/dont-blame-bad-weather-for-

your-aching-back

179. Healing Well: http://news.healingwell.com/index.php?p=news1&id=689584

180. KTRE: http://www.ktre.com/story/25985267/dont-blame-bad-weather-for-your-aching-

back

181. My Fox Orlando: http://www.myfoxorlando.com/story/25985267/dont-blame-bad-


182. WCAX: http://www.wcax.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

183. Sify News: http://www.sify.com/news/weather-doesn-t-cause-low-back-pain-say-

scientists-news-news-ohlmaBahdgccf.html

222

184. Fox Oregon: http://www.kptv.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

185. KXXV: http://www.kxxv.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

186. WPSD Local: http://www.wpsdlocal6.com/story/25985267/dont-blame-bad-weather-


187. My Fox Los Angeles: http://www.myfoxla.com/story/25985267/dont-blame-bad-


188. Wnem: http://www.wnem.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

189. KEYC TV Mankato: http://www.keyc.com/story/25985267/dont-blame-bad-weather-


190. WHLT 22: http://www.whlt.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

191. KATV: http://www.katv.com/story/25985267/dont-blame-bad-weather-for-your-aching-

back

192. CBS 5 AZ: http://www.kpho.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

193. KTIV: http://www.ktiv.com/story/25985267/dont-blame-bad-weather-for-your-aching-

back

194. WAOW: http://www.waow.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

223

195. Oklahoma’s Own: http://www.newson6.com/story/25985267/dont-blame-bad-weather-


196. Kotatv: http://www.kotatv.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

197. Valley News Live: http://www.valleynewslive.com/story/25985267/dont-blame-bad-


198. My Fox Memphis: http://www.myfoxmemphis.com/story/25985267/dont-blame-bad-


199. WXYZ Detroit: http://www.wxyz.com/news/national/study-finds-no-link-between-


200. Independent Mail: http://www.independentmail.com/news/national/study-finds-no-link-

between-certain-weather-conditions-lower-back-pain

201. Irish Health: http://www.irishhealth.com/article.html?id=23849

202. The Indy Channel: http://www.theindychannel.com/news/study-finds-no-link-between-


203. WKRG News: http://ww2.wkrg.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

204. ABC 6: http://www.abc6.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

205. News Plex: http://wn.newsplex.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

224

206. My 13 LA: http://www.my13la.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

207. Be Live: http://phucanpc.com/8120/dont-blame-bad-weather-for-your-aching-back/

208. Lycos News: http://news.lycos.com/entertainment/weather-not-related-to-back-ache-

9ab8817dbfd88f499f11b5e88f498903/

209. WIFR Rockford: http://wn.wifr.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

210. KKTV Sothern Colorado: http://wn.kktv.com/story/25985267/dont-blame-bad-weather-


211. Capital Gazette: http://www.capitalgazette.com/parade/health/does-weather-cause-

aches/article_3ced89f1-7c0c-5259-817b-a13c0e94cdb8.html

212. Cinema Blend: http://www.cinemablend.com/pop/Scientists-Claim-Link-Between-Cold-

Weather-Back-Pain-Nonexistent-65185.html

213. Fox 16: http://www.fox16.com/story/d/story/back-pain-not-caused-by-the-

weather/30094/RvNSiTKnf06Hlp3Tkkr6MA

214. FM News Talk: http://www.971talk.com/news/health/weather-doesnt-cause-aggravate-

back-pain

215. Value Based Care in Rheumatology: http://www.valuebasedrheumatology.com/vbcr-

news/news-feed/1172-back-pain-not-brought-on-by-weather-except-for-trivial-wind-effect

216. Joint Pain 101: http://jointpain101.com/achy-back-pain-isnt-due-to-bad-weather-latest-

study-finds-tech-times/

225

217. India News Hub: http://indianewshub.com/weather-cause-back-pain/

218. Faraday’s Natural Foods and Supplements:

http://www.faradaysnaturalfoods.com/common/news/news_results.asp?task=Headline&id=1

5368&StoreID=EADB2AA619684A9AB9AF9A7D0A20FF81

219. Wild by Nature:

http://www.wildbynature.com/common/news/news_results.asp?task=Headline&id=15368&S

toreID=D272A3B93180420D908E136E9D7E775D

220. Lovelock Pharmacy: https://lovelockpharmacy.com/article.php?id=689584

221. My Center Pharmacy: https://mycenterpharmacy.com/article.php?id=689584

222. US News: http://health.usnews.com/health-news/articles/2014/07/10/dont-blame-bad-


223. Wate: http://www.wate.com/story/25985267/dont-blame-bad-weather-for-your-aching-

back

224. Clinical Research: http://www.clinicalresearch.com/NewsDetail.aspx?id=689584

225. WMBF News: http://www.wmbfnews.com/story/25985267/dont-blame-bad-weather-


226. Jose Marcos – Doencas Reumaticas:

http://doencasreumat.blogspot.com.au/2014_07_11_archive.html

227. 1 Click News: http://1clicknews.com/is-the-weather-to-blame-for-lower-back-pain/

228. The Malay Mail Online: http://m.themalaymailonline.com/features/article/dont-blame-

the-weather-for-lower-back-pain-study-says

226

229. Gulf Bend Center:

http://www.gulfbend.org/poc/view_doc.php?type=news&id=165586&cn=72

230. Priyo News: http://news.priyo.com/2014/07/13/dont-curse-weather-low-back-pain-

113952.html

231. Bakersfield Now: http://wn.bakersfieldnow.com/story/25985267/dont-blame-bad-


232. 0 Hag: http://www.0hag.com/dont-listen-granny-weather-impact-state-bad-back/

233. WLTZ First News: http://www.wltz.com/story/25985267/dont-blame-bad-weather-for-

your-aching-back

234. Daily Health Headlines: http://www.dailyhealthheadlines.com/article/health-

headlines/feel-it-in-your-bones-back-pain-not-linked-with-weather

235. The Health Site: http://www.thehealthsite.com/news/weather-to-blame-for-lower-back-

pain/

236. CTV News: http://www.ctvnews.ca/health/is-the-weather-to-blame-for-lower-back-pain-

1.1911889

237. Astro Awani: http://english.astroawani.com/news/show/is-the-weather-to-be-blamed-

for-lower-back-pain-39770

238. Free Malaysia Today:

http://www.freemalaysiatoday.com/category/leisure/2014/07/14/is-the-weather-to-blame-for-

lower-back-pain/

239. Malaysian Digest: http://malaysiandigest.com/features/509026-don-t-blame-the-

weather-for-lower-back-pain-study-says.html

227

240. International Business Times: http://au.ibtimes.com/articles/559112/20140714/back-

pain-backache-weather-world-health-association.htm#.U8OTEPmSx8E

241. Iafrica: http://lifestyle.iafrica.com/wellness/949058.html

242. The New Age: http://thenewage.co.za/131503-12-53-

Is_the_weather_to_blame_for_lower_back_pain

243. The Roger Hedgecock Show: http://www.rogerhedgecock.com/story/25985267/dont-

blame-bad-weather-for-your-aching-back

244. Reuters UK: http://uk.reuters.com/article/2014/07/14/us-weather-back-pain-

idUKKBN0FJ1SI20140714

245. Huffington Post Canada: http://www.huffingtonpost.ca/2014/07/14/back-pain-causes-

weather_n_5584538.html

246. Ciencias Medicas News: http://elbiruniblogspotcom.blogspot.com.au/2014/07/dont-

blame-bad-weather-for-your-aching.html

247. ABC 40 KRHD: http://www.abc40.com/story/25985267/dont-blame-bad-weather-for-

your-aching-back

248. WITN: http://wn.witn.com/story/25985267/dont-blame-bad-weather-for-your-aching-

back

249. WBTV: http://www.wbtv.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

250. Hon News: http://www.hon.ch/News/HSN/689584.html

228

251. WOWKRV: http://www.wowktv.com/story/25985267/dont-blame-bad-weather-for-

your-aching-back

252. WDAM: http://www.wdam.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

253. Newsday: http://www.newsday.com/news/health/don-t-blame-bad-weather-for-your-

aching-back-1.8755826

254. 14 News: http://www.14news.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

255. WSAV: http://www.wsav.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

256. KPLCTV: http://www.kplctv.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

257. WLOX 13: http://www.wlox.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

258. WGEM: http://www.wgem.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

259. My Fox Nepa: http://www.myfoxnepa.com/story/25985267/dont-blame-bad-weather-


260. WDRB: http://www.wdrb.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

261. WSPA 7: http://www.wspa.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

229

262. Winnipeg Free Press: http://www.winnipegfreepress.com/arts-and-life/life/health/dont-

blame-bad-weather-for-your-aching-back-266581831.html

263. My Fox Wausau: http://www.myfoxwausau.com/story/25985267/dont-blame-bad-


264. KCBD: http://www.kcbd.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

265. News Channel 12: http://www.wjtv.com/story/25985267/dont-blame-bad-weather-for-

your-aching-back

266. News R India: http://newsr.in/n/Health/750jc4162/Weather-to-blame-for-lower-back-

pain.htm

267. WKOW Madison: http://www.wkow.com/story/25985267/dont-blame-bad-weather-for-

your-aching-back

268. Herald Whig: http://www.whig.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

269. West Virginia Illustrated: http://www.wvillustrated.com/story/25985267/dont-blame-

bad-weather-for-your-aching-back

270. The Mercury: http://www.themercury.com.au/news/breaking-news/back-pain-dont-

blame-it-on-the-rain/story-fnj6ehgr-1226984395748

271. WRCB Chattanooga: http://www.wrcbtv.com/story/25985267/dont-blame-bad-weather-


272. Hawaii News Now: http://www.hawaiinewsnow.com/story/25985267/dont-blame-bad-


230

273. KWWL: http://www.kwwl.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

274. ABC Kait 8: http://www.kait8.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

275. My Fox Phoenix: http://www.myfoxphoenix.com/story/25985267/dont-blame-bad-


276. My Fox DC: http://www.myfoxdc.com/story/25985267/dont-blame-bad-weather-for-

your-aching-back

277. WTHR Indiana’s News Leader: http://www.wthr.com/story/25985267/dont-blame-bad-


278. My Fox Boston: http://www.myfoxboston.com/story/25985267/dont-blame-bad-


279. CBS 8: http://www.cbs8.com/story/25985267/dont-blame-bad-weather-for-your-aching-

back

280. My Fox Dallas-Fort Worth: http://www.myfoxdfw.com/story/25985267/dont-blame-


281. WSFA 12: http://www.wsfa.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

282. My Fox Tampa Bay: http://www.myfoxtampabay.com/story/25985267/dont-blame-bad-


283. WSET-TV Lynchburg Danville Roanoke: http://www.wset.com/story/25985267/dont-


231

284. WKRN-TV Nashville: http://www.wkrn.com/story/25985267/dont-blame-bad-weather-


285. Fox 51 WOGX: http://www.wogx.com/story/25985267/dont-blame-bad-weather-for-

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286. News Channel 5: http://www.newschannel5.com/story/25985267/dont-blame-bad-


287. Fox 29 WFLX: http://www.wflx.com/story/25985267/dont-blame-bad-weather-for-

your-aching-back

288. Yahoo! News India: https://in.news.yahoo.com/dont-curse-weather-low-back-pain-

090004253.html

289. 9&10 Northern Michigan’s News Leader:

http://www.9and10news.com/story/25985267/dont-blame-bad-weather-for-your-aching-back

290. The Courant: http://www.courant.com/health/sns-rt-us-weather-back-pain-

20140714,0,296648.story

291. KTBS 3: http://www.ktbs.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

292. Townsville Bulletin: http://www.townsvillebulletin.com.au/news/breaking-news/back-

pain-dont-blame-it-on-the-rain/story-fnjbnvyi-1226984395748

293. KLTV 7: http://www.kltv.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

294. Rocket News: http://www.rocketnews.com/2014/07/feel-it-in-your-bones-back-pain-not-

linked-with-weather/

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295. Yahoo! News UK and Ireland: https://uk.news.yahoo.com/feel-bones-back-pain-not-

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296. WAVE 3 News: http://www.wave3.com/story/25985267/dont-blame-bad-weather-for-

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297. Gold Coast Bulletin: http://www.goldcoastbulletin.com.au/news/breaking-news/back-

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298. KVVU-TV Fox 5 Las Vegas: http://www.fox5vegas.com/story/25985267/dont-blame-


299. Web India 123:

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300. WVVA – The two Virginias: http://www.wvva.com/story/25985267/dont-blame-bad-


301. WFMJ: http://www.wfmj.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

302. Truth Dive: http://truthdive.com/2014/07/11/Weather-doesn-t-cause-low-back-pain-say-

scientists.html

303. KTVN 2 News: http://www.ktvn.com/story/25985267/dont-blame-bad-weather-for-

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304. NBC 2: http://www.nbc-2.com/story/25985267/dont-blame-bad-weather-for-your-

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305. KTEN 10 Texoma: http://www.kten.com/story/25985267/dont-blame-bad-weather-for-

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306. WRBL: http://www.wrbl.com/story/25985267/dont-blame-bad-weather-for-your-

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307. WTOC 11: http://www.wtoc.com/story/25985267/dont-blame-bad-weather-for-your-

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308. KFVS 12: http://www.kfvs12.com/story/25985267/dont-blame-bad-weather-for-your-

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309. Prokerala News: http://www.prokerala.com/news/articles/a472570.html

310. KSWO 7 News Lawton/ Wichita Falls: http://www.kswo.com/story/25985267/dont-


311. ABC 2 WBAY: http://www.wbay.com/story/25985267/dont-blame-bad-weather-for-

your-aching-back

312. Mizo News: http://www.mizonews.net/world/dont-curse-weather-for-low-back-pain/

313. ABC 10 News: http://www.10news.com/news/national/study-finds-no-link-between-


314. Neuro Talk:

http://neurotalk.psychcentral.com/showthread.php?s=77a5572aa77f20b8e90925adf927a025&

p=1082100#post1082100

315. Latest News Link: http://latestnewslink.com/2014/07/weather-not-tied-to-back-pain-

study/

316. Big News Network: http://www.bignewsnetwork.com/index.php/cat/eb75a2fd5e16e873/

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317. Personal Liberty Digest: http://personalliberty.com/study-finds-link-certain-weather-

conditions-lower-back-pain/

318. Cliprender: http://www.cliprender.com/clip/Is-The-Weather-To-Be-Blamed-For-Lower-

Back-Pain%3F

319. Turn to 10: http://ww2.turnto10.com/story/25985267/dont-blame-bad-weather-for-your-

aching-back

320. Focus Italy: http://www.focus.it/ADNKronos/salute-sfatato-legame-meteo-dolore-clima-

non-influenza-mal-di-schiena_C65.aspx

321. Meteo e scienze del cielo e della terra: http://www.meteoweb.eu/2014/07/salute-sfatato-

legame-meteo-dolori-clima-non-influenza-mal-schiena/298772/

322. Australian Doctor: http://www.australiandoctor.com.au/news/latest-news/weather-not-a-

barometer-for-back-pain

323. ABLX Boston: http://www.manewsday.com/national/65203-don-t-listen-to-granny-the-

weather-has-no-impact-on-the-state-of-your-bad-back.html

324. Sina Women Eladies – China: http://eladies.sina.com.tw/getnews.php?newsid=97932

325. Viet Times: http://www.viet-times.com.au/gia-dinh/suc-khoe/1300534-thoi-tiet-khong-

anh-huong-den-chung-dau-lung?device=desktop

326. Tien Phong Online: http://khoe360.tienphong.vn/gia-dinh-suc-khoe/khong-co-bang-

chung-dau-lung-do-thoi-tiet-734237.tpo

327. Path Finder:

http://www.pathfinder.gr/stories/3752169/%CF%80%CE%BF%CE%BD%CE%BF%CF%82

-%CF%83%CF%84%CE%B7-%CE%BC%CE%B5%CF%83%CE%B7-

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328. AArgauer Zeitung: http://www.aargauerzeitung.ch/leben/gesundheit/ist-das-schlechte-

wetter-schuld-am-hexenschuss-128166931

329. Anteka: http://www.apteka.ua/article/299054

330. RMF 24: http://www.rmf24.pl/nauka/news-bole-w-krzyzu-nie-przez-

pogode,nId,1467274

331. Tiscali: http://lifestyle.tiscali.it/salute/feeds/14/07/11/t_16_ADN20140711130058.html

332. TVN Meteo: http://tvnmeteo.tvn24.pl/informacje-pogoda/ciekawostki,49/bole-w-

krzyzu-to-nie-przez-pogode,127818,1,0.html

333. Sante Log: http://www.santelog.com/news/rhumatologie/arthrite-et-lombalgie-une-

question-de-meteo-_12595_lirelasuite.htm

334. Time Turk: http://www.timeturk.com/tr/2014/07/10/buyukanneler-yaniliyor-

olabilir.html#.U8TruPmSx8E

335.Wissenschaft: http://www.wissenschaft-

aktuell.de/artikel/Hexenschuss__Das_Wetter_ist_nicht_schuld1771015589598.html

336. Gazete A24: http://www.gazetea24.com/yerel-basin-haber/buyukanneler-yaniliyor-

olabilir_12387770.html

337. Aponet: http://www.aponet.de/aktuelles/kurioses/20140710-kein-wettereinfluss-auf-

rueckenschmerzen.html

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Dr Daniel Steffens - Curriculum Vitae Page 1 of 4

EDUCATION

DOCTOR OF PHILOSOPHY (2011 - 2015), The George Institute for Global Health, Sydney Medical School, The University of Sydney, Australia. Thesis title: Mechanisms of low back pain. Supervisor: Professor Chris G Maher Main projects: Clinicians’ views on factors that trigger a sudden onset of low back pain. Factors predicting recruitment of participants to an observational study of low back pain

conducted in primary care. Prognosis of chronic low back pain in patients presenting to a private community-based group

exercise program. Does magnetic resonance imaging predict future low back pain? A systematic review. Triggers of an acute onset of low back pain – results of a case-crossover study. Does the weather affect back pain? A case-crossover study. Do MRI findings identify patients with low back pain who respond best to particular

interventions? A systematic review. Triggers for an episode of sudden onset low back pain: Study protocol. BACHELOR OF PHYSIOTHERAPY - HONOURS (2001 - 2005), University of Santa Cruz do Sul, Brazil.

EXPERIENCE (ACADEMIC)

LECTURER, Macquarie University, Department of Chiropractic, Faculty of Science, Australia (2014-present). Subject: Chiropractic 2 – CHIR 311 (Research Methods). Designing, preparing and developing teaching materials. Delivering lectures. Setting and marking assignments.

EXPERIENCE (RESEARCH)

CLINICAL RESEARCH ASSISTANT, Neuroscience Research Australia, University of New South Wales (2015 - present). Project: Standing Tall - A home-based balance exercise program. NHMRC-funded randomised controlled trial involving 500 participants. Administering participants comprehensive physical assessment. Maintaining study database. Delivering study intervention to participants. Developing study materials. RESEARCH ASSISTANT, The George Institute for Global Health, The University of Sydney, Australia (2010 – 2011). Project: Paracetamol for low back pain (PACE). NHMRC-funded randomised controlled trial involving 1650 participants. Recruited and enrolled study clinicians and participants. Provided additional administrative support and carried out general clerical duties. Administered participant’s interviews and prepared assessments. Wrote research manuscript, presentations, reports and ethical submissions. Developed and maintained research databases (Excel, FileMaker Pro). Achievement: Received a discretionary bonus for recognition and reward of exceptional performance.

Address: 4/18 Market Street | Rockdale, Sydney NSW 2216 Mobile: + 61 2 0423 786 695 | E-mail: [email protected]

Dr Daniel Steffens CURRICULUM

VITAE

237


EXPERIENCE (RESEARCH)

RESEARCH ASSISTANT, Faculty of Health Science, The University of Sydney, Australia (2009 – 2010). Project: Prognosis of chronic back pain. One year follow-up study that involved 118 participants presenting to private care. Performed face-to-face and telephone data collection. Performed systematic literature searching. Liaised with data collection sites. Performed data entry and statistical analysis (SPSS). Wrote protocols, ethical documents and scientific papers. Achievement: Completion of the study on time with minimal loss to follow-up. Published

study in relevant scientific journal.

SUPPORT OF JUNIOR RESEARCH STUDENTS

Keira BEILKEN and Vicky DUONG - Does weather affect daily pain levels in patients with acute low back pain? A longitudinal cohort study. Honours Students , Macquarie University - 2015.

Matthew STEVENS - Patients’ and clinicians’ views on triggers for low back pain. Doctor of Philosophy, The University of Sydney – 2014.

Patricia PARREIRA – Nominating triggers for low back pain patients. Doctor of Philosophy, The University of Sydney – 2014.

PUBLICATIONS (FULL PAPER)

DANIEL STEFFENS, Manuela L Ferreira, Jane Latimer, Bart W Koes, Fiona M Blyth, Paulo H Ferreira, Christopher G Maher. What triggers an episode of acute low back pain? A case-crossover study. Arthritis Care & Research, 2015; 67(3):403-10. DANIEL STEFFENS, Chris G Maher, Manuela L Ferreira, Mark J Hancock, Leani SM Pereira, Christopher M Williams, Jane Latimer. Clinician characteristics and operational factors have limited influence on participant recruitment in primary care: Results from an observational study. Journal of Manipulative and Physiological Therapeutics, 2015; xx:1-8. DANIEL STEFFENS, Chris Maher, Qiang Li, Manuela Ferreira, Leani Pereira, Bart Koes, Jane Latimer. Weather does not affect back pain: results from a case-crossover. Arthritis Care & Research, 2014; 66(12):1867-72. DANIEL STEFFENS, Chris Maher. Effectiveness of extracorporeal shock wave therapy in chronic plantar fasciitis. American Journal of Physical Medicine and Rehabilitation, 2014; 2:1-2. DANIEL STEFFENS, Chris Maher, Manuela Ferreira, Mark Hancock, Timothy Glass, Jane Latimer. Clinicians’ views on factors that trigger a sudden onset of low back pain. European Spine Journal, 2014; 23(3):512-9. DANIEL STEFFENS, Mark Hancock, Chris Maher, Jane Latimer, Rob Satchill, Manuela Ferreira, Paulo Ferreira, Melissa Partington, Anna-Louise Bouvier. Prognosis of chronic low back pain in patients presenting to a private community-based group exercise program. European Spine Journal, 2014; 23(1):113-9. DANIEL STEFFENS, Mark Hancock, Chris G Maher, Ciaran Williams, Tue Secher Jensen, Jane Latimer. Does magnetic resonance imaging predict future low back pain? A systematic review. European Journal of Pain, 2013; 18(6):755-65.

238


PUBLICATIONS (FULL PAPER)

DANIEL STEFFENS, Paula R Beckenkamp, Mark Hancock, Dulciane Nunes Paiva, Jennifer A Alison, Sergio S Menna-Barreto. Activity level predicts 6-minute walk distance in healthy older females: an observational study. Physiotherapy, 2013; 99(1):21-6. DANIEL STEFFENS, Manuela L Ferreira, Christopher G Maher, Jane Latimer, Bart W Koes, Fiona M Blyth and Paulo H Ferreira. Triggers for an episode of sudden onset low back pain: study protocol. BMC Musculoskeletal Disorders, 2012; 13:7. DANIEL STEFFENS, Chris Maher. Conflicting findings on effectiveness of low level laser therapy for tendinopathty. British Journal of Sports Medicine, 2011; 45:459. Antonio MV Silva, Luis U Signori, Guilherme C Torres, DANIEL STEFFENS, Rodrigo DM Plentz. Neuromuscular electrical stimulation versus strength training in elderly women. Geriatria & Gerontologia, 2008; 2(1):12-16 [Portuguese]. DANIEL STEFFENS, Paula R Beckenkamp, Isabella M Albuquerque, Dulciane N Paiva, Serigio SM Barreto. Occupational exposure to tobacco dust – effects on the respiratory system. Pulmão RJ, 2007; 16:86-90 [Portuguese].

PUBLICATIONS (PROCEEDINGS)

DANIEL STEFFENS, Manuela Ferreira, Jane Latimer, Paulo H Ferreira, Bart W Koes, Fiona Blyth, Qiang Li, Chris Maher. What triggers an episode of low back pain? Results of a case-crossover study. Proceedings XIII International Back Pain Forum. Campos do Jordao, Brazil, 2014. p52. DANIEL STEFFENS, Chris Maher, Qiang Li, Manuela Ferreira, Leani Pereira, Bart W Koes, Jane Latimer. Could the weather triggers an episode of low back pain? A case-crossover study. Proceedings XIII International Back Pain Forum. Campos do Jordao, Brazil, 2014. p81. DANIEL STEFFENS, Mark Hancock, Chris G Maher, Ciaran Williams, Tue S Jensen, Jane Latimer. Does magnetic resonance imaging predict future low back pain? A systematic review. Proceedings Pain in Europe VIII. Florence, Italy, 2013. p1117. DANIEL STEFFENS, Manuela Ferreira, Chris Maher, Jane Latimer, Bart Koes, Fiona Blyth, Paulo Ferreira. Does the method of training of recruiting clinicians influence recruitment to a low back pain case-crossover study. Proceedings Odense International Forum XII. Odense, Denmark, 2012. p.178. DANIEL STEFFENS, Manuela Ferreira, Chris Maher, Jane Latimer, Bart Koes, Fiona Blyth, Paulo Ferreira. Clinician’s views on triggers for sudden onset low back pain. Proceedings Odense International Forum XII. Odense, Denmark, 2012. p.195. DANIEL STEFFENS, Paula R Beckenkamp, Mark Hancock, Dulciane N Paiva, Sergio S Menna-Barreto, Jennifer A Alison. Six minute walk distance in healthy elderly active and sedentary female. Proceedings Australian Physiotherapy Association Biennial Conference 2011. Brisbane, Australia, 2011. p.126. DANIEL STEFFENS, Mark J Hancock, Rob Satchill, Manuela Ferreira, Paulo Ferreira, Chris G Maher, Melissa Partington, Ana-Louise Bouvier. Prognosis of patients with chronic low back pain presenting to a private functional group exercise program. Proceedings Australian Physiotherapy Association Biennial Conference. Brisbane, Australia, 2011. p.146.

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RESEARCH GRANTS AND AWARDS

COTUTELLE AWARD (2011 – 2015), jointly awarded degree between The University of Sydney (Australia) and the Federal University of Minas Gerais (Brazil). TRAVEL GRANT (2014), Research Student Grant Scheme (RSGS), School of Public Health, Sydney Medical School, The University of Sydney (AUD$ 2602.00). TOP BEST ABSTRACT (2013), EFIC-Pain in Europe VII Congress. Florence, Italy. TRAVEL GRANT (2013), Research Student Grant Scheme (RSGS), School of Public Health, Sydney Medical School, The University of Sydney (AUD$ 1200.00). TRAVEL GRANT (2012), Postgraduate Research Support Scheme (PRSS), School of Public Health, Sydney Medical School, The University of Sydney (AUD$ 1020.74).

REVIEWER (SCIENTIFIC ARTICLES)

JOURNAL OF PHYSIOTHERAPY MANUAL THERAPY WORLD CONFEDERATION FOR PHYSICAL THERAPY BMC MUSCULOSKELETAL DISORDERS JOURNAL OF MEDICAL INTERNET RESEARCH PROTOCOLS

REFEREES

PROF. CHRIS G MAHER (PhD Supervisor) Director, Musculoskeletal Division. The George Institute for Global Health, The University of Sydney Telephone: +61 2 9657 0382 E-mail: [email protected]

A/PROF. MARK HANCOCK (Previous employer) Senior Lecturer, Musculoskeletal physiotherapy. Macquarie University Telephone: +61 2 9850 6622 E-mail: [email protected]

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Documents

Daniel Steffens - UFMGSupervisors’ Statement As supervisors of Daniel Steffens’ doctoral work, we certify that we consider his thesis “Mechanisms of Low Back Pain” to be suitable