title: Predicting long-term functional limitations among back pain patients in primary care settings.
abstract: To identify predictors of back-related long-term functional limitations, 1213 adult enrollees of a Health Maintenance Organization (HMO) in Washington state were interviewed about a month after a consultation for back pain in a primary care setting in 1989-1990, and followed each year thereafter. Out of 100 factors documented at the one-month assessment, measures of somatization, depression, functional limitations, and pain were the strongest predictors of two-year modified Roland-Morris score among a random subsample of 569 subjects. A multiple regression model containing the Symptom Checklist Depression and Somatization scores, the one-month modified Roland-Morris score and the number of pain days in the past six months explained about 30% of the variance in the outcome. Using recursive partitioning, a very simple model was developed to identify patients at high risk of sustaining long-term significant functional limitations. The regression model and the recursive partitioning model were successfully tested in a fresh sample of patients (n = 644). Clinical application of the recursive partitioning model and methodological aspects of this study are discussed.
authors.affiliation: Department of Epidemiology, University of Washington, Seattle 98195, USA.
authors.forename: C E
authors.initials: CE
authors.lastname: Dionne
authors.forename: T D
authors.initials: TD
authors.lastname: Koepsell
authors.forename: M
authors.initials: M
authors.lastname: Von Korff
authors.forename: R A
authors.initials: RA
authors.lastname: Deyo
authors.forename: W E
authors.initials: WE
authors.lastname: Barlow
authors.forename: H
authors.initials: H
authors.lastname: Checkoway
mesh_terms: D000328:Adult; D000368:Aged; D000704:Analysis of Variance; D001416:Back Pain / Q000145:classification / Q000523:psychology / Q000534:rehabilitation*; D005260:Female; D005500:Follow-Up Studies; D006279:Health Maintenance Organizations; D006801:Humans; D008297:Male; D008432:Mathematical Computing; D008875:Middle Aged; D015233:Models, Statistical; D011237:Predictive Value of Tests; D011320:Primary Health Care; D012044:Regression Analysis; D012307:Risk Factors; D016896:Treatment Outcome; D014861:Washington