Prediction of arrhythmic events after myocardial infarction based on signal-averaged electrocardiogram and ejection fraction

Background: Trials on implantable cardioverter-defibrillators (ICD) for patients after acute myocardial infarction (AMI) have highlighted the need for risk assessment of arrhythmic events (AE). The aim of this study was to evaluate risk predictors based on a novel approach of interpreting signal-averaged electrocardiogram (SAECG) and ejection fraction (EF). Methods: SAECG, interpreted with a new index, and EF were prospectively evaluated to predict AE in 144 patients with AMI. Results: During the mean follow-up period of 4.1 years, 19 AE occurred. The new SAECG index showed a sensitivity of 84 %, a specificity of 62%, a positive predictive value (PPV) of 25%, and a negative predictive value (NPV) of 96%. A combination of a normal new SAECG index and an EF > 35% resulted in a sensitivity of 100%, a specificity of 47%, a PPV of 22%, and a NPV of 100%; this corresponded to an AE incidence rate of 0%. When both tests were abnormal, the AE incidence rate was 21.3%. Conclusions: This is the first contemporary study reporting predictive values based on a combination of SAECG and EF. If confirmed in an appropriately designed and powered trial, this novel approach might be used to identify both patients at very low risk for AE not requiring further risk assessment and patients at high Fisk in whom ICD implantation can be considered without further risk assessment.