The importance of radiating leg pain in assessing health outcomes among patients with low back pain. Results from the Veterans Health Study.

Abstract

Cross-sectional data were analyzed from the Veterans Health Study, an observational study of patients receiving ambulatory care. To develop a method of stratifying patients with low back pain by combining patient reports of radiating leg pain with the results of straight leg raising tests. Four hundred thirty-four participants with low back pain were identified through patient reports of ever having had low back pain, of low back pain that began more than 3 months ago, and of a health-care visit for low back pain in the past year. Four hundred twenty-eight patients with low back pain were included in the current analysis. Participants were mailed a health-related quality of life questionnaire and had an interview that included a low back pain questionnaire and a straight leg raising test. Patients' reports of radiating leg pain and results of the straight leg raising tests were combined into four hierarchical groups. This stratification was evaluated in relation to responses to the health-related quality of life questionnaire, localized low back pain, disability, and use of medical services. The intensity of localized low back pain and disability increased from Group 1 (low back pain alone) to Group 4 (pain below knee with positive straight leg raising test result), whereas health-related quality of life decreased. Group 4 patients were 5.1 times more likely than were Group 1 patients to use medications for low back pain (95% confidence interval 1.2, 22.9), 6.8 times more likely to have a spinal magnetic resonance study (95% confidence interval, 2.7, 17.2), and 3.9 times more likely to have surgery (95% confidence interval, 1.3, 11.4). The method of measuring correlation performs well in identifying patients with different levels of localized low back pain intensity, health-related quality of life, and use of services. It may be useful in studies of health outcomes, in clinical trials, and in predicting demands on health care resources.