Article

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.

Langue : ANGLAIS