Background: Work disability is common in patients with coronary artery disease and adversely affects both economic well-being and quality of life. The purpose of this study was to construct a model to predict premature departure from the work force of patients with coronary disease and to validate this model prospectively in an independent cohort of patients.
Methods and results: We enrolled 1,252 coronary disease patients referred for diagnostic cardiac catheterization who were less than age 65, employed, and without prior coronary angioplasty or coronary bypass surgery. Medical, functional, psychological, economic, and job-related variables were measured at the time of baseline diagnostic cardiac catheterization, and all patients were followed for 1 year. Three hundred twelve patients underwent percutaneous transluminal coronary angioplasty (PTCA) within 60 days of catheterization, and 449 had coronary artery bypass graft surgery (CABG) within 60 days of catheterization. The remaining 491 patients were treated with initial medical therapy. Logistic regression was used to develop a multivariable model for predicting 1-year work status in the training sample patients (872 patients enrolled between March 1986 and February 1989). This model was then validated in the independent prospective test sample (380 patients enrolled between March 1989 and June 1990). Eight factors were independent predictors of departure from the work force: lower initial functional status (as assessed by the Duke Activity Status Index), followed by older age, black race, presence of congestive heart failure, lower education level, presence of extracardiac vascular disease, poorer psychological status, and lower job classification. Standard clinical variables provided only 20% of the total predictive information available from the model about follow-up work outcomes, whereas functional measures provided 27%, and demographic and socioeconomic measures provided 45%. In the test sample, the area under the receiver operating characteristic curve for the model predictions was 0.74, compared with 0.80 in the training sample, and model predictions agreed well with observed prevalences of return to work. After adjustment for baseline imbalances, there was no significant difference in 1-year return-to-work rates among the patients receiving initial PTCA or CABG therapy versus initial medical therapy.
Conclusions: Patients with coronary disease who are at high risk for premature departure from the work force can be accurately identified from a combination of medical and nonmedical risk factors. The model developed in this study provides a tool to identify patients at high risk for premature loss from the work force. Such patients may benefit from special multidimensional intervention programs designed to preserve work status. Our data show that revascularization with either PTCA or CABG is not, by itself, sufficient to accomplish this goal.