The aim of this study was to extract and combine non-invasive risk parameters from the signal-averaged electrocardiogram (SAECG) and heart rate variability (HRV) based on 24-hour ambulatory electrocardiography to optimize the prognostic value for arrhythmic events after acute myocardial infarction. A prospective series of 553 men < 66 years of age enrolled in the Post-Infarction Late Potential study were analyzed. Within 2 to 4 weeks after acute myocardial infarction, all patients underwent SAECG and 24-hour ambulatory electrocardiography before hospital discharge. During 6 months of followup, 25 patients (4.5%) experienced arrhythmic events (sustained ventricular tachycardia, n = 11; ventricular fibrillation, n = 7; sudden cardiac death, n = 7). The predictive power of SAECG and HRV parameters was assessed using a Cox proportional-hazards model. In HRV analysis, the most significant differences between patients with and without arrhythmic events were observed for the beat-to-beat parameter root-meansquare of successive RR differences [RMSSD]): 25.7 +/- 16.9 ms in patients with arrhythmic events versus 34.1 +/- 18.6 ms in patients free of arrhythmic events (p = 0.004). Time domain analysis of the SAECG showed the QRS duration to be most significantly different in both patient groups: 106.4 +/- 18.7 ms (arrhythmic events) versus 95.3 +/- 18.7 ms (no arrhythmic events) (p = 0.001). Based on the Cox regression model, RMSSD and QRS duration were demonstrated to be independent significant risk factors (regression coefficient for QRS duration: cq = 0.014 +/- 0.006 ms(-1), p = 0.014; for RMSSD: cr = -0.041 +/- 0.016 ms(-1), p = 0.009). Based on the regression coefficients, an analytic risk model was developed describing the arrhythmic risk as a function of QRS duration, RMSSD, and time after infarction. We conclude that the combination of beat-to-beat changes of heart rate measured by RMSSD and QRS duration from the SAECG enhances noninvasive risk stratification after myocardial infarction.