Abstract
There has recently been a resurgence of interest in electrocardiogram-based (ECG-based) parameters in predicting Sudden Cardiac Death (SCD) risk. Accurate and timely SCD predictions are essential clinical practice for physicians to provide effective prevention and treatment. An ECG is a non-invasive and inexpensive diagnostic test, and has been firmly established as a clinical tool for assessing the risk of cardiac disease. The electrocardiographic signal derived from the ECG recording consists of a distinctive waveform that depicts the electrical activity of the heart, which can be analyzed for the identification of abnormalities in the heart rhythm. The parameter or characteristic found in the ECG signal might be important for predicting the SCD. A number of systematic reports by expert meetings and review articles in indexed journals identified ECG-based parameters as QRS duration, QT interval, Signal Average ECG (SAECG), T-wave alternan (TWA), Heart Rate Variability (HRV), Heart Rate Turbulence (HRT), T-peak to T-end (Tpe), fragmented QRS complexes (fQRS), and Early Repolarization (ER). This article reviews the mechanism and morphology of these parameters, which may potentially have a role to play in a future algorithm designed to identify early signs of SCD. As of now, none of the ECG-based parameters have been found to be sufficiently stable to predict the SCD risk. Nevertheless, the combination of two or more of the parameters listed, as suggested in many studies, may become a useful component for predicting SCD in the future.