Artificial Intelligence–Derived Electrocardiographic Age Predicts Mortality in Adults With Congenital Heart Disease
Delta-age, the difference between AI-ECG and chronological age, is an independent predictor of all-cause mortality in ACHD.
Authors
- Jennifer Dugan (ORCID: https://orcid.org/0000-0002-1483-3201)
- Donnchadh O’Sullivan (ORCID: https://orcid.org/0000-0002-9492-8576)
- Talha Niaz (ORCID: https://orcid.org/0000-0003-2186-584X)
- Kathryn E. Mangold (ORCID: https://orcid.org/0000-0001-7048-2699)
- Malini Madhavan (ORCID: https://orcid.org/0000-0002-2831-4568)
- Scott Anjewierden (ORCID: https://orcid.org/0000-0001-5542-1599)
- Francisco Lopez‐Jimenez
- Zachi Itzhak Attia (ORCID: https://orcid.org/0000-0002-9706-7900)
- William R. Miranda (ORCID: https://orcid.org/0000-0001-8864-8474)
- Alexander C. Egbe (ORCID: https://orcid.org/0000-0002-8810-3631)
- Luke James Burchill (ORCID: https://orcid.org/0000-0001-9786-1840)
- Samuel J. Asirvatham (ORCID: https://orcid.org/0000-0001-9835-5536)
- Katia Bravo‐Jaimes (ORCID: https://orcid.org/0000-0001-7745-7162)
- Heidi M. Connolly (ORCID: https://orcid.org/0000-0003-0666-0344)
- Paul A Friedman
Institutions
- Mayo Clinic (US)
- Jacksonville College (US)
- WinnMed (US)
- Mayo Clinic in Arizona (US)
- Mayo Clinic in Florida (US)
Publication Details
- Journal
- JACC Advances
- Published
- 2025-05-14
- DOI
- https://doi.org/10.1016/j.jacadv.2025.101777
- Citations
- 4
- Primary Topic
- Congenital Heart Disease Studies
- Type
- article
- Field-Weighted Citation Impact
- 5.42