Artificial intelligence-enabled analysis of handheld single-lead electrocardiograms to predict incident atrial fibrillation: an analysis of the VITAL-AF randomized trial
Whether artificial intelligence (AI) analysis of single-lead ECG (1 L ECG) can predict incident AF is unknown. In the VITAL-AF trial (ClinicalTrials.gov NCT03515057, registered 2/24/2021) of primary care patients aged ≥65 years undergoing handheld 1 L ECG screening, we tested three AI approaches to incident AF prediction, and compared the best model to the CHARGE-AF risk score. In a test set of 4,221 individuals, a published AI model trained using single standard ECG leads ("1 L ECG-AI") provided similar 2-year AF discrimination to models trained with VITAL-AF data. In the full VITAL-AF sample of 15,694 individuals without prevalent AF (2-year incident AF 3.1%), 1 L ECG-AI with age/sex (1 L ECG-AI AS) had comparable discrimination (area under the receiver operating characteristic curve [AUROC] 0.695[0.637-0.742]; average precision [AP] 0.060[0.050-0.078]) to CHARGE-AF (AUROC 0.679[0.623-0.730]; AP 0.062[0.052-0.080], AUROC p = 0.46, AP p = 0.92). Net reclassification improvement was favorable versus age ≥65 years (0.27[0.22-0.32]). 1 L ECG-AI may increase efficiency and reach of AF screening.
Authors
- Jennifer E. Ho (ORCID: https://orcid.org/0000-0002-7987-4768)
- Christopher D. Anderson (ORCID: https://orcid.org/0000-0002-0053-2002)
- Daniel E. Singer (ORCID: https://orcid.org/0000-0001-6145-4848)
- Shinwan Kany (ORCID: https://orcid.org/0000-0001-8113-733X)
- Leila H. Borowsky (ORCID: https://orcid.org/0000-0001-7498-4450)
- Shaan Khurshid (ORCID: https://orcid.org/0000-0002-2840-4539)
- Jeffrey M. Ashburner (ORCID: https://orcid.org/0000-0002-5600-3492)
- Mostafa A. Al‐Alusi (ORCID: https://orcid.org/0000-0002-9359-1641)
- Thomas Sommers (ORCID: https://orcid.org/0000-0002-1300-8234)
- Sam Friedman (ORCID: https://orcid.org/0000-0002-0688-2169)
- Steven J. Atlas (ORCID: https://orcid.org/0000-0002-2297-9614)
- Mahnaz Maddah (ORCID: https://orcid.org/0000-0002-9837-6000)
- David D. McManus (ORCID: https://orcid.org/0000-0002-9343-6203)
- Steven A. Lubitz
- Patrick T. Ellinor
Institutions
- Broad Institute (US)
- Brigham and Women's Hospital (US)
- Heart Rhythm Society (US)
- Beth Israel Deaconess Medical Center (US)
- Harvard University (US)
- Universität Hamburg (DE)
- University of Massachusetts Chan Medical School (US)
- Massachusetts General Hospital (US)
- University Medical Center Hamburg-Eppendorf (DE)
- German Centre for Cardiovascular Research (DE)
- Mass General Brigham (US)
- Massachusetts Institute of Technology (US)
Publication Details
- Journal
- npj Digital Medicine
- Published
- 2025-11-26
- DOI
- https://doi.org/10.1038/s41746-025-02164-2
- Citations
- 2
- Primary Topic
- ECG Monitoring and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 2.78
Funders
- American Heart Association
- Bristol-Myers Squibb
- Pfizer
- European Commission
- Deutsche Forschungsgemeinschaft
- National Institutes of Health