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October 5, 2025European Heart Journal - Digital HealthOpen Access

AI-ECG-derived biological age as a predictor of mortality in cardiovascular and acute care patients

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Authors

DPDaniel PavlukFTFabian TheurlSPSamuel Pröll

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Overview

Analysis reveals AI-ECG biological age predicts long-term mortality in patients with cardiovascular disease and acute conditions, highlighting clinical utility.

Key Points

  • AI-ECG age is a strong predictor of long-term mortality in cardiovascular patients and those with acute illnesses.
  • Patients with a positive Δ-age of +8 years have a 1.45 higher risk of 10-year mortality compared to those with a negative Δ-age of -8 years.
  • The study analyzed ECG data from 48,950 patients using deep learning and multivariable Cox models to assess risks.
  • Saliency maps show the model's sensitivity, indicating the P-wave as a crucial input for predictions.

Cite This Study

Pavluk et al. (2025) studied this question.

synapsesocial.com/papers/68e24e6bd6d66a53c247391fhttps://doi.org/10.1093/ehjdh/ztaf109
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Also Consider

Synapse has enriched one closely related paper. Consider it for comparative context:

  1. 1Global Burden of Cardiovascular Diseases and Risk Factors, 1990–20192020 · 11,687 citations