Multivariable prediction models for the recovery of and claim closure related to post-collision neck pain and associated disorders

Chiropractic & Manual Therapies

Research

J. David Cassidy¹  Maja Stupar²  Pierre Côté³  Heather M. Shearer⁴  Robert J. Brison⁵  Linda J. Carroll⁶  Eleanor Boyle⁷ 

[1] Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada;Institute for Disability and Rehabilitation Research, Ontario Tech University, Oshawa, Canada;Division of Graduate Education and Research, Canadian Memorial Chiropractic College, Toronto, Canada;Institute for Disability and Rehabilitation Research, Ontario Tech University, Oshawa, Canada;Faculty of Health Sciences, Ontario Tech University, Ontario, Canada;Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada;Institute for Disability and Rehabilitation Research, Ontario Tech University, Oshawa, Canada;Holland Bloorview Kids Rehabilitation Hospital, Toronto, Canada;Kingston General Hospital Research Inst, Kingston, Canada;Department of Emergency Medicine, Faculty of Health Sciences, Queen’s University, Kingston, Canada;School of Public Health, University of Alberta, Edmonton, Canada;Thunderbird Partnership Foundation, Bothwell, ON, UK;

关键词: Neck pain;    Whiplash;    Clinical prediction model;    Rehabilitation;    Disability;    Health recovery;   

DOI  :  10.1186/s12998-023-00504-1

 received in 2023-02-02, accepted in 2023-07-24,  发布年份 2023

来源: Springer

【 摘 要 】

ObjectiveFew clinical prediction models are available to clinicians to predict the recovery of patients with post-collision neck pain and associated disorders. We aimed to develop evidence-based clinical prediction models to predict (1) self-reported recovery and (2) insurance claim closure from neck pain and associated disorders (NAD) caused or aggravated by a traffic collision.MethodsThe selection of potential predictors was informed by a systematic review of the literature. We used Cox regression to build models in an incident cohort of Saskatchewan adults (n = 4923). The models were internally validated using bootstrapping and replicated in participants from a randomized controlled trial conducted in Ontario (n = 340). We used C-statistics to describe predictive ability.ResultsParticipants from both cohorts (Saskatchewan and Ontario) were similar at baseline. Our prediction model for self-reported recovery included prior traffic-related neck injury claim, expectation of recovery, age, percentage of body in pain, disability, neck pain intensity and headache intensity (C = 0.643; 95% CI 0.634–0.653). The prediction model for claim closure included prior traffic-related neck injury claim, expectation of recovery, age, percentage of body in pain, disability, neck pain intensity, headache intensity and depressive symptoms (C = 0.637; 95% CI 0.629–0.648).ConclusionsWe developed prediction models for the recovery and claim closure of NAD caused or aggravated by a traffic collision. Future research needs to focus on improving the predictive ability of the models.

【 授权许可】

CC BY   
© Chiropractic and Osteopathic College of Australasia, European Academy of Chiropractic, The Royal College of Chiropractors, Nordic Institute of Chiropractic and Clinical Biomechanics and BioMed Central Ltd. 2023

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