A Preliminary Risk Stratification Model for Individuals with Neck Pain


Journal Article

© 2015 John Wiley & Sons, Ltd. Introduction: The aim of the present study was to identify predictive characteristics related to patients with neck impairments who have a high risk of a poor prognosis (lowest functional recovery compared to visit utilization) as well as those who are at low risk of a poor prognosis (highest functional recovery compared to visit utilization). Methods: A retrospective cohort of 3,137 patients with neck pain who were seen for physiotherapy care was included in the study. All patients were seen at physiotherapy clinics in the United States and were provided with care in a manner in which the physiotherapists felt was appropriate and necessary. Univariate and multivariate multinomial regression analyses were used to identify significant patient characteristics predictive of treatment response. Results: Statistically significant predictors of high-risk categorization included longer duration of symptoms, surgical history and lower comparative levels of disability at baseline. Statistically significant predictors of low-risk categorization were younger age, shorter duration of symptoms, no surgical history, fewer comorbidities and higher comparative disability levels of function at baseline. Discussion: Few studies have analysed risk stratification models for neck pain, and the findings of the present study suggest that predictors of poor success are similar to those in most musculoskeletal prognostic models. Limitations of the study included those inherent in secondary analysis and the inability to identify the diagnoses of the patients. Conclusions: Future research should continue to examine the variables predictive of treatment response in patients with neck pain.

Full Text

Duke Authors

Cited Authors

  • Cook, C; Rodeghero, J; Cleland, J; Mintken, P

Published Date

  • January 1, 2015

Published In

Volume / Issue

  • 13 / 3

Start / End Page

  • 169 - 178

Electronic International Standard Serial Number (EISSN)

  • 1557-0681

International Standard Serial Number (ISSN)

  • 1478-2189

Digital Object Identifier (DOI)

  • 10.1002/msc.1098

Citation Source

  • Scopus