Heart age estimated using explainable advanced electrocardiography.
Heart age estimated using explainable advanced electrocardiography.
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DOI：
10.1038/s41598-022-13912-9
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发表时间：
2022-06-14
影响因子：
4.6
通讯作者：
Ugander, Martin
中科院分区：
文献类型：
--
作者：
Lindow, Thomas;Palencia-Lamela, Israel;Schlegel, Todd T.;Ugander, Martin
通过贝叶斯和人工智能两种方法来估计传达心血管风险的心电(CG)心脏年龄。我们假设，10-S 12导联心电的可解释措施可以成功预测贝叶斯5分钟心电心脏年龄。我们对健康受试者和有心血管风险或已证实患有心脏病的患者的心电图进行了高级分析。用回归模型预测患者标准的静息10-S 12导联心电图的贝叶斯5分钟心电年龄。分析了5分钟与10分钟S心电心电年龄的差异，以及10分钟心电S心电心龄与时间年龄(心脏年龄差)的差异。总共纳入2,771名受试者(n = 1682名健康志愿者，n = 305名有心血管危险因素，n = 784名有心血管疾病)。总体而言，10-S心脏年龄与5分钟心脏年龄有很好的一致性(R2 = 0.94p <； 0.001，平均 ± SD偏差0.0 ± 5.1年)。健康人的心脏年龄差为0.0 ± 5.7年，有心血管危险因素的患者为7.4 ± 7.3年(p <； 0.001)，心血管疾病患者为14.3 ± 9.2年(p <； 0.001)。基于已知的心电测量，可以根据10-S 12导联心电以透明和可解释的方式准确估计心脏年龄，而不需要深度神经网络类型的人工智能技术。心脏年龄差距随着心血管风险和疾病的增加而显著增加。
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-s 12-lead ECG could successfully predict Bayesian 5-min ECG Heart Age. 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-min ECG Heart Ages from their standard, resting 10-s 12-lead ECGs. The difference between 5-min and 10-s ECG Heart Ages were analyzed, as were the differences between 10-s ECG Heart Age and the chronological age (the Heart Age Gap). In total, 2,771 subjects were included (n = 1682 healthy volunteers, n = 305 with cardiovascular risk factors, n = 784 with cardiovascular disease). Overall, 10-s Heart Age showed strong agreement with the 5-min Heart Age (R2 = 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). Heart Age can be accurately estimated from a 10-s 12-lead ECG in a transparent and explainable fashion based on known ECG measures, without deep neural network-type artificial intelligence techniques. The Heart Age Gap increases markedly with cardiovascular risk and disease.
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