A New Biomarker of Aging Derived From Electrocardiograms Improves Risk Prediction of Incident Cardiovascular Disease.

Journal: JACC. Advances
Published Date: May 13, 2025

Abstract

BACKGROUND: A biomarker of cardiovascular aging, derived from a deep learning algorithm applied to digitized 12-lead electrocardiograms, has recently been introduced. This biomarker, δ-age, is defined as the difference between predicted electrocardiogram age and chronological age.

Authors

  • Tom Wilsgaard
    Department of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway; Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. Electronic address: tom.wilsgaard@uit.no.
  • Wayne Rosamond
    Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
  • Henrik Schirmer
    Department of Cardiology, Akershus University Hospital, Oslo, Norway.
  • Haakon Lindekleiv
    Department of Radiology, University Hospital of North Norway, Tromsø, Norway.
  • Zachi I Attia
    Department of Cardiovascular Medicine, Mayo Clinic College of Medicine, Rochester, Minnesota, USA.
  • Francisco Lopez-Jimenez
    Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA.
  • David A Leon
    Department of Community Medicine, UiT The Arctic University of Norway, Tromsø 9037, Norway; Department of Non-communicable Diseases Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London WC1E 7HT, UK; International Laboratory for Population and Health, National Research University, Higher School of Economics, Moscow, Russia.
  • Olena Iakunchykova
    Department of Psychology, University of Oslo, Oslo, Norway.

Keywords

No keywords available for this article.

External Resources

Popular Topics
Recent Journals