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

OBJECTIVE: Few 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 n...

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Detalles Bibliográficos
Autores principales: Stupar, Maja, Côté, Pierre, Carroll, Linda J., Brison, Robert J., Boyle, Eleanor, Shearer, Heather M., Cassidy, J. David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10464149/
https://www.ncbi.nlm.nih.gov/pubmed/37626364
http://dx.doi.org/10.1186/s12998-023-00504-1
Descripción
Sumario:OBJECTIVE: Few 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. METHODS: The 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. RESULTS: Participants 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). CONCLUSIONS: We 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12998-023-00504-1.