Abstract 15714: Prediction of Sudden Cardiac Death With Automated High-Throughput Analysis of T-Wave Heterogeneity in Standard 12-Lead Electrocardiogram

Abstract

Introduction: Noninvasive identification of patients at risk for sudden cardiac death (SCD) remains a major clinical challenge. Abnormal ventricular repolarization is associated with increased risk of lethal ventricular arrhythmias and SCD. Hypothesis: We investigated the hypothesis that spatial repolarization heterogeneity can identify patients at risk for SCD in general population. Methods: Spatial R-, J- and T-wave heterogeneities (RWH, JWH and TWH, respectively) were automatically analyzed with second central moment technique from standard digital 12-lead ECGs in 5618 adults (46% men; age 50.9±12.5 yrs.) who took part in Health 2000 Study, an epidemiological survey representative of the entire Finnish adult population. During average follow-up of 7.7±1.4 years, a total of 72 SCDs occurred. Thresholds of RWH, JWH and TWH were based on optimal cutoff points from ROC curves. Results: Increased RWH, JWH and TWH (Fig.1) in left precordial leads (V4-V6) were univariately associated with SCD (P<0.001, each). When adjusted with clinical risk markers (age, gender, BMI, systolic blood pressure, cholesterol, heart rate, left ventricular hypertrophy, QRS duration, arterial hypertension, diabetes, coronary heart disease and previous myocardial infarction) JWH and TWH remained as independent predictors of SCD. Increased TWH (≥102μV) was associated with a 1.9-fold adjusted relative risk (95% confidence interval [CI]: 1.2 - 3.1; P=0.011) and increased JWH (≥123μV) with a 2.0-fold adjusted relative risk for SCD (95% CI: 1.2 - 3.3; P=0.004). When both TWH and JWH were above threshold, the adjusted relative risk for SCD was 3.2-fold (95% CI: 1.7 - 6.2; P<0.001). When all heterogeneity measures (RWH, JWH and TWH) were above threshold, the risk for SCD was 3.7-fold (95% CI: 1.6 - 8.6; P=0.003). Conclusions: Automated measurement of spatial J- and T-wave heterogeneity enables analysis of high patient volumes and is able to stratify SCD risk in general population.