Determinants of artificial intelligence electrocardiogram-derived age and its association with cardiovascular events and mortality: a systematic review and meta-analysis.
systematic_review · Level I
Where this comes from
- Record sourced from PubMed, PMID 40442323.
- Also identified by DOI 10.1038/s41746-025-01727-7 and PMC identifier 12122673.
- Licence recorded as CC BY-NC-ND.
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Abstract
Artificial intelligence (AI)-ECG-derived age (AI-ECG age) and Heart Delta Age (HDA)-the difference between AI-ECG and chronological age-are emerging tools for assessing cardiovascular health. We systematically searched PubMed, Embase, Web of Science, and Scopus from inception through September 2024. Seventeen original studies utilizing AI algorithms to measure HDA and cardiovascular risk factors, outcomes, or mortality were included. Data were pooled using random- and fixed-effects models for meta-analysis. Hypertension and diabetes mellitus emerged as the most prevalent factors contributing to higher HDA, while cardiac diseases including myocardial infarction and heart failure demonstrated the most significant impact. Pooled analysis revealed a significant association between elevated HDA and increased risks of all-cause mortality (hazard ratio [HR] 1.62, 95% confidence interval [CI] 1.49-1.77) and cardiovascular mortality (HR 2.12, 95% CI 1.71-2.63). HDA could enhance existing risk models and play a critical role in primary healthcare prevention.