Development of a screen for predicting clinical outcomes in patients with work-related upper extremity disorders

This study prospectively examined the extent to which a set of medical, physical, ergonomic, occupational psychosocial, and individual psychosocial variables would predict clinical outcome associated with a diverse set of work-related upper extremity disorders in recently diagnosed individuals. This investigation was designed to develop a tool for use in a clinical setting to assist in identifying patients at risk for poorer outcome. Outcome was measured at 1, 3, and 12 months apm completely a baseline questionnaire. Outcome status was based on a median split of a standardized composite index (symptoms, function, workdays lost, and mental health). Logistic regression indicated that predictors of poorer outcome at 1 month were: upper extremity comorbidity (risk ratio [RR], 1.58), pain severity (RR, 1.45), ergonomic risk exposure (RR, 1.07), four job support (RR 1.03), and pain coping style (RR, 1.54). At 3 months, poorer outcome was predicted by: symptom severity (RR, 10.46), job stress (RR, 1.20), and pain coping style (RR, 1.98). The number of prior treatments/providers (RR, 1.77), past recommendation for surgery (RR, 6.43), and pain coping style were found to predict poorer outcome at 12 months. Sensitivity and specificity, respectively for the models were 77.4% and 71.8% at 1 month, 80. 6% and 82.4 % at 3 months, and 80.6% and 83.3% at 12 months. indicate that baseline measures of ergonomic and psychosocial stress, pain severity, and Pain coping style predict clinical outcome at shorter. intervals, whereas number of past treatments/providers recommendation for surgery and pain coping style predict longer-term outcome. The resulting prognostic screen providers a simple tool that assesses the multidimensional nature of work-related upper extremity disorders and predicts clinical outcome. Furthermore, the findings suggest the importance of early intervention that addresses both physical and psychosocial stressors at work. Specific recommendations to reduce the impact of observed risk factors are discussed.