Risk Stratification After Myocardial Infarction Using Signal-Averaged Electrocardiographic Criteria Adjusted for Sex, Age, and Myocardial Infarction Location

Author:

Savard Pierre1,Rouleau Jean-Lucien1,Ferguson John1,Poitras Nicole1,Morel Patrick1,Davies Richard F.1,Stewart Duncan J.1,Talajic Mario1,Gardner Martin1,Dupuis Robert1,Lauzon Claude1,Sussex Bruce1,Potvin Louise1,Warnica Wayne1

Affiliation:

1. From the Institut de génie biomédical, Ecole Polytechnique, Université de Montréal, and Centre de recherche, Hôpital du Sacré-Coeur, Montréal, Québec (P.S., P.M.); Département de Médecine, Institut de Cardiologie de Montréal (J.-L.R., N.P., M.T.); Memphis (Tenn) Vascular Foundation (J.F.); Department of Medicine, Ottawa (Ontario) Heart Institute (R.F.D.); Department of Medicine, Royal Victoria Hospital, Montréal (D.J.S.); Department of Medicine, Victoria General Hospital, Nova Scotia (M...

Abstract

Background The objectives were to investigate the factors influencing signal-averaged ECGs (SAECGs) recorded in patients after myocardial infarction (MI) and to develop criteria for predicting arrhythmic events (AEs) that account for these factors. Methods and Results SAECGs were recorded 5 to 15 days after MI in 2461 patients without bundle-branch block. The duration (QRSd), terminal potential (VRMS), and terminal duration (LAS) of the filtered QRS were measured. During follow-up (17±8 months), AEs (arrhythmic death; ventricular tachycardia, VT; ventricular fibrillation, VF) occurred in 80 patients (3.3%). Receiver operating characteristic curves showed that QRSd discriminated patients with all types of AEs, but VRMS and LAS discriminated only VT patients; QRSd minus LAS also discriminated AE patients. Sex, age, and MI location significantly affected the SAECG; survivors without VT or VF were divided into subgroups (2 sex×4 age×2 MI), and QRSd values exceeding the 70th percentile in each subgroup predicted AEs with a sensitivity of 65.4%. An unadjusted QRSd criterion showed the same overall sensitivity and specificity but with less uniform values for each subgroup. A Cox model was constructed by use of multiple prognostic indicators, and in rank order, QRSd, previous MI, and Killip class were predictive of AEs. Conclusions SAECG adjustments for sex, age, and MI location did not improve sensitivity and specificity but produced a more uniform predictive performance. The proposed criteria are based only on QRSd, because late potentials (VRMS and LAS) did not discriminate patients with sudden death. Duration of high-level activity during QRS (QRSd−LAS) can predict AEs, suggesting that the arrhythmogenic substrate involves a large mass of myocardium.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Physiology (medical),Cardiology and Cardiovascular Medicine

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