Prognostic Factors of a Favorable Outcome Following a Supervised Exercise Program for Soldiers With Sub-acute and Chronic Low Back Pain
Prognostic Factors of a Favorable Outcome Following a Supervised Exercise Program for Soldiers With Sub-acute and Chronic Low Back Pain
Low back pain (LBP) encompasses heterogeneous patients unlikely to respond to a unique treatment. Identifying sub-groups of low back pain may help to improve treatment outcomes. Our objective was to identify variables associated with a favorable outcome in soldiers with sub-acute and chronic LBP participating in a multi-station full-body supervised exercise program. The results obtained may permit generation of potential treatment effect modifiers that will eventually have to be validated before being recommended for clinical practice.
All participants took part in the 6-week exercise program, as well as in the two evaluation sessions (pre- and post- exercise program). At the initial evaluation, subjects completed forms and questionnaires on sociodemographics, symptomatology, comorbidities, work restrictions, pain and functional limitations and fear-avoidance beliefs. A physiotherapist measured their lumbar and hip mobility, conducted diagnostic and pain provocation tests and assessed endurance of the trunk muscles. Following the initial evaluation, subjects took part in the 6-week multi-station full-body supervised exercise program (2 to 3 sessions per week). The Oswestry disability questionnaire (ODI) was completed at the initial and at the final evaluations. The change in ODI score following the program was considered the principal measure reflecting favorable or unfavorable outcome.
An improvement of 50% in the initial ODI score was considered the reference standard to determine a favorable outcome. Univariate associations with favorable outcome were tested using chi-square or paired t-tests. Variables that showed between-group (favorable/unfavorable) differences were entered into a logistic regression after determining the sampling adequacy. Finally, continuous variables were dichotomized and the sensitivity, specificity and positive and negative likelihood ratios were determined for the model and for each variable.
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