ArticleEuropean heart journal. Digital health2023
Heart age gap estimated by explainable advanced electrocardiography is associated with cardiovascular risk factors and survival.
Article in European heart journal. Digital health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Associations of Biological Age and Heart Age Accelerations With New-Onset Stroke in Individuals With Cardiovascular-Kidney-Metabolic Syndrome Stages 0-3: Evidence From a Chinese Longitudinal Study.Journal of clinical hypertension (Greenwich, Conn.) · 2026Article
- Comparison of Artificial Intelligence-Derived Heart Age with Chronological Age Using Normal Sinus Electrocardiograms in Patients with No Evidence of Cardiac Disease.Journal of clinical medicine · 2025Article
- Determinants of artificial intelligence electrocardiogram-derived age and its association with cardiovascular events and mortality: a systematic review and meta-analysis.NPJ digital medicine · 2025Article
- Advanced electrocardiography heart age: a prognostic, explainable machine learning approach applicable to sinus and non-sinus rhythms.European heart journal. Digital health · 2025Article
- Biological heart and brain ageing in subjects with cardiovascular diseases.Frontiers in cardiovascular medicine · 2025Article
- Association between cardiovascular disease risk, regional brain age gap, and cognition in healthy adults.Frontiers in aging neuroscience · 2025Article
- Usefulness of Atherogenic Indices for Predicting High Values of Avoidable Lost Life Years Heart Age in 139,634 Spanish Workers.Diagnostics (Basel, Switzerland) · 2024Article
- Machine learning of brain-specific biomarkers from EEG.EBioMedicine · 2024Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Aims: Deep neural network artificial intelligence (DNN-AI)-based Heart Age estimations have been presented and used to show that the difference between an electrocardiogram (ECG)-estimated Heart Age and chronological age is associated with prognosis. An accurate ECG Heart Age, without DNNs, has been developed using explainable advanced ECG (A-ECG) methods. We aimed to evaluate the prognostic value of the explainable A-ECG Heart Age and compare its performance to a DNN-AI Heart Age. Methods and results: Both A-ECG and DNN-AI Heart Age were applied to patients who had undergone clinical cardiovascular magnetic resonance imaging. The association between A-ECG or DNN-AI Heart Age Gap and cardiovascular risk factors was evaluated using logistic regression. The association between Heart Age Gaps and death or heart failure (HF) hospitalization was evaluated using Cox regression adjusted for clinical covariates/comorbidities. Among patients [ Conclusion: A-ECG Heart Age Gap is associated with cardiovascular risk factors and HF hospitalization or death. Explainable A-ECG Heart Age Gap has the potential for improving clinical adoption and prognostic performance compared with existing DNN-AI-type methods.
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