Prediction of depressive disorder following myocardial infarction data from the Myocardial INfarction and Depression-Intervention Trial (MIND-IT)

BACKGROUND: Depression following myocardial infarction (MI) is associated with complicated cardiac rehabilitation, non-compliance and poor prognosis. Whether depression following MI can be predicted from variables routinely assessed during hospitalization for MI is unknown. METHODS: Using data from the Myocardial INfarction and Depression-Intervention Trial (MIND-IT), we identified 2,177 MI patients (mean age 63 years; 23% female). Patients were randomly divided into a derivation and a validation sample. In the derivation sample, we analyzed variables potentially associated with the development of post-MI depressive disorder, which were tested in the validation sample. RESULTS: In the year following MI, 18.5% suffered from depressive disorder (ICD-10 criteria). In a multivariate model, factors associated with depression were younger age (OR 1.94; CI 1.38-2.74), hypercholesterolemia (OR 1.68; CI 1.08-2.61), the use of calcium channel blockers at discharge (OR 1.80; CI 1.20-2.71), and left ventricular ejection fraction (LVEF) (OR 4.14 for patients with LVEF <30%; CI (2.42-7.10). The derived predictors were tested in the validation sample. The final model yielded two clinical predictors, i.e., younger age and severe LV-dysfunction, which correctly predicted post-discharge depression status in 82.9% of the MI patients. The model yielded a high negative predictive value (89%). A positive depression questionnaire (BDI) during hospitalization increased the positive predictive value of 23% to 52%. CONCLUSIONS: During hospitalization for MI and using a two-step strategy with common clinical variables, i.e., younger age, severe LV-dysfunction and BDI score during hospitalization, it is possible to identify MI patients with a high risk for subsequent development of depression