Identifying patients at risk of becoming disabled because of low-back pain. The Vermont Rehabilitation Engineering Center predictive model

Spine (Phila Pa 1976). 1991 Jun;16(6):605-7. doi: 10.1097/00007632-199106000-00001.


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.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Adult
  • Aged
  • Back Pain / epidemiology*
  • Disability Evaluation
  • Expert Systems*
  • Humans
  • Middle Aged
  • Models, Statistical*
  • Predictive Value of Tests
  • Prospective Studies
  • Risk Factors