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. 2024 Oct 9;6(1):45-54.
doi: 10.1093/ehjdh/ztae075. eCollection 2025 Jan.

Advanced electrocardiography heart age: a prognostic, explainable machine learning approach applicable to sinus and non-sinus rhythms

Zaidon S Al-Falahi  1   2 , Todd T Schlegel  3   4 , Israel Palencia-Lamela  1 , Annie Li  1 , Erik B Schelbert  5 , Louise Niklasson  5 , Maren Maanja  3 , Thomas Lindow  1   6   7 , Martin Ugander  1   3
Affiliations

Advanced electrocardiography heart age: a prognostic, explainable machine learning approach applicable to sinus and non-sinus rhythms

Zaidon S Al-Falahi et al. Eur Heart J Digit Health. .

Abstract

Aims: An explainable advanced electrocardiography (A-ECG) Heart Age gap is the difference between A-ECG Heart Age and chronological age. This gap is an estimate of accelerated cardiovascular aging expressed in years of healthy human aging, and can intuitively communicate cardiovascular risk to the general population. However, existing A-ECG Heart Age requires sinus rhythm. We aim to develop and prognostically validate a revised, explainable A-ECG Heart Age applicable to both sinus and non-sinus rhythms.

Methods and results: An A-ECG Heart Age excluding P-wave measures was derived from the 10-s 12-lead ECG in a derivation cohort using multivariable regression machine learning with Bayesian 5-min 12-lead A-ECG Heart Age as reference. The Heart Age was externally validated in a separate cohort of patients referred for cardiovascular magnetic resonance imaging by describing its association with heart failure hospitalization or death using Cox regression, and its association with comorbidities. In the derivation cohort (n = 2771), A-ECG Heart Age agreed with the 5-min Heart Age (R 2 = 0.91, bias 0.0 ± 6.7 years), and increased with increasing comorbidity. In the validation cohort [n = 731, mean age 54 ± 15 years, 43% female, n = 139 events over 5.7 (4.8-6.7) years follow-up], increased A-ECG Heart Age gap (≥10 years) associated with events [hazard ratio, HR (95% confidence interval, CI) 2.04 (1.38-3.00), C-statistic 0.58 (0.54-0.62)], and the presence of hypertension, diabetes mellitus, hypercholesterolaemia, and heart failure (P ≤ 0.009 for all).

Conclusion: An explainable A-ECG Heart Age gap applicable to both sinus and non-sinus rhythm associates with cardiovascular risk, cardiovascular morbidity, and survival.

Keywords: Accelerated aging; Advanced ECG analysis; ECG; Machine learning; Risk prediction.

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Conflict of interest statement

Conflict of interest: Z.S.A., T.L., I.L.-P., A.L., E.B.S., L.N., and M.M.: none; T.T.S. is owner and founder of Nicollier-Schlegel SARL, which performs ECG interpretation consultancy using software that can quantify the advanced ECG measures used in the current study. T.T.S. and M.U. are the owners and founders of Advanced ECG Systems, a company that is developing commercial applications of advanced ECG technology used in the current study.

Figures

Graphical Abstract
Graphical Abstract
Figure 1
Figure 1
Left panel: scatter plot showing the relationship between the 10-s, A-ECG Heart Age and the 5-min A-ECG Heart Age in the derivation cohort. The R2 value was 0.91 (P < 0.001). Right panel: Bland–Altman plot showing the difference between the 10-s A-ECG Heart Age and 5-min A-ECG Heart Age in relation to the mean of both ECG heart ages. The agreement between methods is strong, with minimal deviation from the identity line (dashed) or bias (0.0 ± 6.7 years).
Figure 2
Figure 2
A-ECG Heart Age gap in healthy individuals (left, orange), individuals with cardiovascular (CV) risk factors (middle, dark grey), and patients with CV disease (right, navy blue). On average, there is a negligible difference between Heart Age and chronological age in healthy individuals, whereas the gap is increased in individuals at CV risk and highest for those with overt CV disease.
Figure 3
Figure 3
Time-to-event analysis for individuals with A-ECG Heart Age gap < 10 years (dense line) vs. those with an A-ECG Heart Age gap≥10 years (dashed line) for hospitalization for heart failure or death in the external validation cohort.
Figure 4
Figure 4
Restricted cubic splines plot showing the continuously increasing HR for death or hospitalization for heart failure with increasing A-ECG heart age gap. The solid line indicates the HR with the shaded area indicating the 95% confidence interval, the dashed line is set at a HR of 1.
Figure 5
Figure 5
Workflow summary of 5-min A-ECG Heart Age and 10-s A-ECG Heart Age derivation and validation.
See this image and copyright information in PMC

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