You could be reading the full-text of this article now if you...

If you have access to this article through your institution,
you can view this article in

Identifying Patients at Risk of Becoming Disabled Because of Low-Back Pain: The Vermont Rehabilitation Engineering Center Predictive Model.

CATS-BARIL, WILLIAM L. PhD; FRYMOYER, JOHN W. MD
Spine:
EUROPEAN EDITION: PDF Only
Abstract

A predictive risk model of low-back pain (LBP) disability was developed by a panel of six experts in the fields of chronic pain and disability. It comprised 28 factors organized into eight categories: job, psychosocial, injury, diagnostic, demographic, medical history, health behaviors, and anthropometric characteristics and was administered as a 15-minute written questionnaire. The model was tested prospectively on 250 patients (age range, 18-65 years) attending two secondary-care low-back clinics. Disability, as predicted by the model, was compared with 1) actual disability assessed 3 and 6 months later; 2) predictions of disability made by the attending physicians; and 3) predictions obtained from an empirically derived model. These results showed that 1) the expert-generated risk model had a predictive accuracy of 89% and did better in predicting disability than the physicians across all samples and 2) the empirically weighted model did best of all (91% predictive accuracy), suggesting that the expert model used appropriate factors but that the weights assigned to these factors by the panel of experts could be improved.

(C) Lippincott-Raven Publishers.