Prediction of adverse events after acute myocardial infarction: derivation and external validation of an extended CHA₂DS₂-VASc score model.

Abstract

The CHA₂DS₂-VASc score predicts poor prognosis in patients with acute myocardial infarction (AMI), with or without atrial fibrillation. In this observational study, we aimed to evaluate the CHA₂DS₂-VASc score by itself and extended with clinical data to predict adverse events in patients after AMI. In this longitudinal observational study, we used a cohort of 955 patients hospitalised for AMI at Västmanland County Hospital, Västerås, Sweden, to derive prediction models. The CHA₂DS₂-VASc score alone and combined with clinical data (systolic blood pressure, creatinine level, ST-segment elevation and diuretic use at discharge) was analysed using Cox regression to evaluate the risk of major adverse events (MAE), defined as all-cause death or hospitalisation due to recurrent MI, heart failure or ischaemic stroke. Discriminatory performance was presented as the time-dependent area under the curve (tdAUC). The prediction models were validated in 416 patients with AMI hospitalised at Uppsala University Hospital, Uppsala, Sweden. During a median of 2.5 years, 287 (30.1%) patients experienced MAE. CHA₂DS₂-VASc scores of 2, 4 and 6 were associated with fourfold, ninefold and 18-fold increases in the relative risk of MAE, respectively, with a tdAUC of 0.76 at a 2-year follow-up. Extending the CHA₂DS₂-VASc score with clinical data significantly improved the prediction model (p<0.001), yielding a tdAUC of 0.81. The models performed well in the validation cohort, with satisfactory calibration and tdAUC values of 0.70-0.78. The addition of clinical data to the CHA₂DS₂-VASc score was superior to a model with CHA₂DS₂-VASc alone in predicting adverse events in patients after AMI, and the model performed well in external validation.