Heart age estimated using explainable advanced electrocardiography
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Abstract
Background Electrocardiographic (ECG) Heart Age conveying cardiovascular risk has been estimated by both Bayesian and artificial intelligence approaches. We hypothesised that explainable measures from the 10-second 12-lead ECG could successfully predict Bayesian 5-min ECG Heart Age. Methods Advanced analysis was performed on ECGs from healthy subjects and patients with cardiovascular risk or proven heart disease. Regression models were used to predict patients’ Bayesian 5-minute ECG Heart Ages from their standard, resting 10-second 12-lead ECGs. The difference between 5-min and 10-second ECG Heart Ages were analyzed, as were the differences between 10-second ECG Heart Age and the chronological age (the Heart Age Gap). Results In 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 (R 2 =0.94, p<0.001, mean±SD bias 0.0±5.1 years). The Heart Age Gap 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 in patients with cardiovascular disease (p<0.001). Conclusions 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 Heart Age Gap increases markedly with cardiovascular risk and disease.
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