Risk stratification by analysis of electrocardiographic morphology following acute coronary syndromes

Abstract

Patients who have suffered an acute coronary syndrome (ACS) are at elevated risk of future adverse events, including fatal arrhythmias or myocardial infarction. Risk stratification--he identification of high-risk patients--s an important step in determining who is most likely to benefit from aggressive treatments. We propose a new automated risk stratification technique that uses the long-term electrocardiographic data routinely recorded in the days following an ACS. Data obtained from clinical drug trials indicates that our technique, called MV-DF (morphologic variability diagnostic frequencies), can significantly improve prognostication for ACS patients. Patients with MV-DF values in the highest quartile show a more than five-fold elevated risk of death in the 90 days following a non-ST-elevation ACS. We also propose techniques to construct models of the dynamics of cardiac behavior. Preliminary results suggest that such techniques may be useful for short-term prediction of fatal arrhythmias. Our results suggest that long-term ECG-based risk assessment techniques--n particular, methods incorporating information about morphologic variability--re an effective and practical way to select appropriate treatment options for cardiovascular disease patients.