Risk stratification of patients with low back pain seen in physical therapy practice.

Journal Article

A secondary analysis of a retrospective cohort was conducted using data obtained from a commercial outcomes database.To identify predictive characteristics related to patients with lumbar impairments who have a high risk of a bad prognosis (lowest functional recovery compared to visit utilization) as well as those who are at low risk of a bad prognosis (highest functional recovery compared to visit utilization).Lumbar impairments are highly prevalent and routinely cause people to seek medical care, including physiotherapy. Most prognostic studies focus solely on good outcomes but do not factor in the intensity of care needed to achieve the outcome. Understanding care intensity needed per outcome achieved could help assign appropriate care quantities.Data from 6379 patients with lumbar impairments were analyzed to determine predictive characteristics that identify patients who either have a low or high risk of a bad prognosis to physiotherapy care. Multinomial regression was used to identify significant patient characteristics predictive of treatment response.Statistically significant predictors for high risk categorization included older age, longer duration of symptoms, surgical history, current use of medications, lower levels of disability at baseline, and insurance categorization. Statistically significant predictors of low risk categorization included younger age, male gender, shorter duration of symptoms, no surgical history, higher levels of disability at baseline, and insurance status.Selected variables were associated with both poor and good recovery. Further research on prognosis, efficacy of physiotherapy care, and cost appear warranted for patients with lumbar impairments.

Full Text

Duke Authors

Cited Authors

  • Rodeghero, JR; Cook, CE; Cleland, JA; Mintken, PE

Published Date

  • December 2015

Published In

Volume / Issue

  • 20 / 6

Start / End Page

  • 855 - 860

PubMed ID

  • 25936467

Electronic International Standard Serial Number (EISSN)

  • 1532-2769

International Standard Serial Number (ISSN)

  • 1356-689X

Digital Object Identifier (DOI)

  • 10.1016/j.math.2015.04.007

Language

  • eng