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Artificial intelligence—derived electrocardiographic age gap as a predictor of mortality after coronary revascularization: prognostic value and short-term intra-patient variability
0
Zitationen
7
Autoren
2026
Jahr
Abstract
Aims: The artificial intelligence (AI)-derived electrocardiographic (ECG) age gap-the difference between AI-predicted ECG age and chronological age-is an emerging biomarker of biological ageing linked to mortality. This study assessed its prognostic value for short- and long-term mortality after coronary artery bypass grafting (CABG) or percutaneous coronary intervention (PCI), addressing model bias in ageing cohorts and short-term intra-patient variability. Methods and results: < 0.005). Conclusion: The AI-derived ECG age gap independently predicts mortality after revascularization, but substantial short-term variability necessitates serial monitoring for reliable clinical use.
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