The Clinical Relevance of ECG Parameters in the Prediction of Cardiac Mortality: A Comprehensive Review

Abstract

About half of all heart disease deaths are caused by cardiac arrest, making it one of the major causes of mortality in prosperous countries. When confronted with potentially fatal arrhythmias, implanted preventive cardioverter defibrillators significantly improve survival chances. However, this is only possible if high-risk patients who are prone to spontaneous cardiac arrest are identified beforehand. The current analysis examines the most recent findings regarding the use of surface electrocardiogram (ECG) data to predict sudden cardiac arrest. Here, we provide a comprehensive overview of the literature on non-invasive ECG techniques for predicting these kinds of cardiovascular crises. Several electrocardiographic risk stratification methods, including T-wave alternans, signal-averaged ECG, T-peak-to-end variation, early repolarization, an extension of the QT interval, QRS duration, QRS cluster patterns, and Holter monitoring, have been reviewed and analysed. These ECG results have shown to be useful as first screening instruments. Nonetheless, no single ECG measure has shown to be an effective technique for classifying individuals based on their risk of sudden cardiac arrest to date. Nevertheless, one or more of these prospective SEM metrics might potentially be important in intricate risk categorization schemes.