Heart age estimated using explainable advanced electrocardiography

Abstract

BackgroundElectrocardiographic (ECG) Heart Age conveying cardiovascular risk has been estimated by both Bayesian and artificial intelligence approaches. We hypothesized that explainable measures from the 10-second 12-lead ECG could successfully predict Bayesian ECG Heart Age.MethodsAdvanced analysis was performed on ECGs from healthy subjects and patients with cardiovascular risk or proven heart disease. Regression models were used to predict a Bayesian 5-minute ECG Heart Age from the standard resting 10-second 12-lead ECG. The difference between 10-second ECG Heart Age and chronological age was compared.ResultsIn total, 2,771 subjects were included (n=1682 healthy volunteers, n=305 with cardiovascular risk factors, n=784 with cardiovascular disease). Overall, 10-second Heart Age showed strong agreement with the 5-minute Heart Age (R2=0.94, p<0.001, mean±SD bias 0.0±5.1 years). The difference between 10-second ECG Heart Age and chronological age was 0.0±5.7 years in healthy individuals, 7.4±7.3 years in subjects with cardiovascular risk factors (p<0.001), and 14.3±9.2 years for patients with cardiovascular disease (p<0.001).ConclusionsECG Heart Age can be accurately estimated from a 10-second 12-lead ECG in a transparent and explainable fashion based on known ECG measures, without artificial intelligence techniques. The difference between ECG Heart Age and chronological age increases markedly with cardiovascular risk and disease.