Early predictors of chronic work disability associated with carpal tunnel syndrome: a longitudinal workers' compensation cohort study.
BACKGROUND
The study objectives were to identify early predictors of chronic work disability associated with carpal tunnel syndrome (CTS) and to test the hypothesis that variables from each of several domains (sociodemographic, clinical, work-related, and psychosocial) would add unique predictive information.


METHODS
Washington State workers were interviewed 18 days (median) after submitting a new workers' compensation claim for CTS. Baseline predictors of chronic work disability (> or =180 days of work disability compensation in the year after claim submission) were examined for workers who had at least 1 day of disability compensation (N = 899).


RESULTS
Baseline demographic variables, symptom severity, functional limitations, lack of job accommodation, job physical demands, job psychosocial conditions, and worker psychosocial characteristics predicted chronic disability bivariately. Each domain of variables added significantly to the prediction of chronic disability. The final multivariable model had fair ability to discriminate individuals with versus without chronic disability (cross-validated area under the ROC curve = 0.76).


CONCLUSIONS
Sociodemographic, clinical, work-related, and worker psychosocial factors early in a claim contribute unique information to the prediction of subsequent work disability associated with CTS.
Turner
Judith A
JA
Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, Washington 98195, USA. jturner@u.washingotn.edu
Franklin
Gary
G
Fulton-Kehoe
Deborah
D
Sheppard
Lianne
L
Wickizer
Thomas M
TM
Wu
Rae
R
Gluck
Jeremy V
JV
Egan
Kathleen
K
Stover
Bert
B
D000203:Activities of Daily Living; D000328:Adult; D002349:Carpal Tunnel Syndrome / Q000453:epidemiology / Q000503:physiopathology*; D002908:Chronic Disease; D004185:Disability Evaluation; D006233:Persons with Disabilities / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D016015:Logistic Models; D008137:Longitudinal Studies; D008297:Male; D009784:Occupational Diseases / Q000453:epidemiology / Q000503:physiopathology*; D011237:Predictive Value of Tests; D011446:Prospective Studies; D012372:ROC Curve; D012959:Socioeconomic Factors; D014861:Washington / Q000453:epidemiology; D014942:Workers' Compensation / Q000706:statistics & numerical data*