Heart failure & cardiomyopathies

Predicting Heart Failure From 12-Lead ECGs Using AI: A HeartShare/AMP-HF Pooled Cohort Analysis

J Am Coll CardiolPublished Pooled cohort study

Authors' conclusion

The addition of ECG-AI to PREVENT-HF improved discrimination of near-term HF risk.

Study context

Population
Participants of the Framingham Heart Study, Multi-Ethnic Study of Atherosclerosis and Cardiovascular Health Study with data for both ECG-AI and PREVENT-HF
Participants
14,126 participants
Exposure
ECG-AI added to PREVENT-HF vs PREVENT-HF alone
Outcome
Incident HF prediction (Harrell's C-statistic and net reclassification improvement)
Follow-up
1, 3, 5 and 10 years
Methodological detailspooled data from 3 cohorts (Framingham Heart Study, MESA, Cardiovascular Health Study)
  • Pooled data from 3 cohorts (Framingham Heart Study, MESA, Cardiovascular Health Study)

Main finding

As reported in the abstract

Net reclassification improvement, ECG-AI added to PREVENT-HF

1-directional NRI at PREVENT-HF threshold 10%

0.086 to 0.125

1-directional NRI at PREVENT-HF threshold 20%

0.327 to 0.403

Positive composite ECG-AI screen: higher risk of developing heart failure (HF) vs negative screen

10- to 20-fold

Observational data: associations, not effects.

Further findings

OutcomeECG-AI LEFECG-AI DDComposite ECG-AIPREVENT-HF
Positive screening rates2.9%11.1%11.9%
Score ≥10%Not reported in the abstractNot reported in the abstractNot reported in the abstract25.1%ECG-AI LEF, ECG-AI DD, Composite ECG-AI: not reported in the abstract
Score ≥20%Not reported in the abstractNot reported in the abstractNot reported in the abstract5.8%ECG-AI LEF, ECG-AI DD, Composite ECG-AI: not reported in the abstract

Incident HF and death

Incident HF
7.7%
Death
15.1%

Original publication

Predicting Heart Failure From 12-Lead ECGs Using AI: A HeartShare/AMP-HF Pooled Cohort Analysis. J Am Coll Cardiol. Published 8 November 2025. doi:10.1016/j.jacc.2025.10.065

Summarised from the published abstract; every number is checked against it

Get them every week

New studies on this topic in My Week and in your Monday e-mail.

We e-mail you a sign-in link and a code. No password, no spam.