Unbound MEDLINE

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

  • Publisher Full Text
  • 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 32-40

    MeSH

    Adolescent
    Adult
    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 Article
    Randomized Controlled Trial

    Language

    eng

    PubMed ID

    22879443