Which prognostic factors for low back pain are generic predictors of outcome across a range of recovery domains?
Abstract
BACKGROUND
Recovery from low back pain (LBP) is multidimensional and requires the use of multiple-response (outcome) measures to fully
reflect these many dimensions. Predictive prognostic variables that are present or stable in all or most predictive models
that use different outcome measures could be considered "universal" prognostic variables.
OBJECTIVE
The aim of this study was to explore the potential of universal prognostic variables in predictive models for 4 different
outcome measures in patients with mechanical LBP.
DESIGN
Predictive modeling was performed using data extracted from a randomized controlled trial. Four prognostic models were created
using backward stepwise deletion logistic, Poisson, and linear regression.
METHODS
Data were collected from 16 outpatient physical therapy facilities in 10 states. All 149 patients with LBP were treated with
manual therapy and spine strengthening exercises until discharge. Four different measures of response were used: Oswestry
Disability Index and Numeric Pain Rating Scale change scores, total visits, and report of rate of recovery.
RESULTS
The set of statistically significant predictors was dependent on the definition of response. All regression models were significant.
Within both forms of the 4 models, meeting the clinical prediction rule for manipulation at baseline was present in all 4
models, whereas no irritability at baseline and diagnosis of sprains and strains were present in 2 of 4 of the predictive
models.
LIMITATIONS
The primary limitation is that this study evaluated only 4 of the multiple outcome measures that are pertinent for patients
with LBP.
CONCLUSIONS
Meeting the clinical prediction rule was prognostic for all outcome measures and should be considered a universal prognostic
predictor. Other predictive variables were dependent on the outcomes measure used in the predictive model.
Links
Authors
Cook CE, Learman KE, O'Halloran BJ, Showalter CR, Kabbaz VJ, Goode AP, Wright AA
Institution
Division of Physical Therapy, Walsh University, 2020 East Maple, North Canton, OH 44720, USA. ccook@walsh.edu
Source
Physical therapy 93:1 2013 Jan pg 32-40MeSH
AdolescentAdult
Aged
Aged, 80 and over
Decision Support Techniques
Disability Evaluation
Female
Humans
Linear Models
Logistic Models
Low Back Pain
Male
Middle Aged
Physical Therapy Modalities
Poisson Distribution
Predictive Value of Tests
Prognosis
Young Adult
Pub Type(s)
Journal ArticleRandomized Controlled Trial
Language
eng
PubMed ID
22879443
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