Background and Aims: AI-enhanced 12-lead ECG can detect a range of structural heart diseases (SHDs) but has a limited role in community-based screening. We developed and externally validated a noise-resilient single-lead AI-ECG algorithm that can detect SHD and predict the risk of their development using wearable/portable devices. Methods: Using 266,740 ECGs from 99,205 patients with paired echocardiographic data at Yale New Haven Hospital, we developed ADAPT-HEART, a noise-resilient, deep-learning algorithm, to detect SHD using lead I ECG. SHD was defined as a composite of LVEF<40%, moderate or severe left-sided valvular disease, and severe LVH. ADAPT-HEART was validated in four community hospitals in the US, and the population-based cohort of ELSA-Brasil. We assessed the model's performance as a predictive biomarker among those without baseline SHD across hospital-based sites and the UK Biobank. Results: The development population had a median age of 66 [IQR, 54-77] years and included 49,947 (50.3%) women, with 18,896 (19.0%) having any SHD. ADAPT-HEART had an AUROC of 0.879 (95% CI, 0.870-0.888) with good calibration for detecting SHD in the test set, and consistent performance in hospital-based external sites (AUROC: 0.852-0.891) and ELSA-Brasil (AUROC: 0.859). Among those without baseline SHD, high vs. low ADAPT-HEART probability conferred a 2.8- to 5.7-fold increase in the risk of future SHD across data sources (all P<0.05). Conclusions: We propose a novel model that detects and predicts a range of SHDs from noisy single-lead ECGs obtainable on portable/wearable devices, providing a scalable strategy for community-based screening and risk stratification for SHD.

Mr. Khunte and Dr. Khera are the coinventors of U.S. Provisional Patent Application No. 63/428,569. Dr. Khera is the coinventor of U.S. Pending Patent Application No. 63/346,610, and is the co-founder of Ensight-AI with Dr. Krumholz. Dr. Khera is the coinventor of U.S. Provisional Pending Patent Applications WO2023230345A1, US20220336048A1, 63/484,426, 63/508,315, 63/580,137, 63/606,203, 63/619,241, and 63/562,335 all unrelated to current work, and is a co-founder of Evidence2Health, a precision health platform for evidence-based care. He is also an associate editor at JAMA, and received support from the National Heart, Lung, and Blood Institute of the National Institutes of Health (under awards R01AG089981, R01HL167858, and K23HL153775) and the Doris Duke Charitable Foundation (under award, 2022060). He also receives research support, through Yale, from Bristol-Myers Squibb, Novo Nordisk, and BridgeBio. Dr. Oikonomou receives support from the National Heart, Lung, and Blood Institute of the National Institutes of Health (under award F32HL170592). He is an academic co-founder of Evidence2Health LLC, a co-inventor in patent applications (18/813,882, 17/720,068, 63/619,241, 63/177,117, 63/580,137, 63/606,203, 63/562,335, US11948230B2 , US20210374951A1), has been a consultant for Caristo Diagnostics Ltd and Ensight-AI Inc, and has received royalty fees from technology licensed through the University of Oxford, outside the submitted work. Dr. Krumholz works under contract with the Centers for Medicare & Medicaid Services to support quality measurement programs, was a recipient of a research grant from Johnson & Johnson, through Yale University, to support clinical trial data sharing; was a recipient of a research agreement, through Yale University, from the Shenzhen Center for Health Information for work to advance intelligent disease prevention and health promotion; collaborates with the National Center for Cardiovascular Diseases in Beijing; receives payment from the Arnold & Porter Law Firm for work related to the Sanofi clopidogrel litigation, from the Martin Baughman Law Firm for work related to the Cook Celect IVC filter litigation, and from the Siegfried and Jensen Law Firm for work related to Vioxx litigation; chairs a Cardiac Scientific Advisory Board for UnitedHealth; was a member of the IBM Watson Health Life Sciences Board; is a member of the Advisory Board for Element Science, the Advisory Board for Facebook, and the Physician Advisory Board for Aetna; and is the co-founder of Hugo Health, a personal health information platform, and co-founder of Refactor Health, a healthcare AI-augmented data management company, and Ensight-AI, Inc. All other authors declare no relevant competing interests.

The study was supported, in part, by research funding from Bristol Myers Squibb to Yale. Dr. Khera was supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health (under awards R01AG089981, R01HL167858, and K23HL153775) and the Doris Duke Charitable Foundation (under award 2022060). Dr. Oikonomou was supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health (under award F32HL170592). The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

The Yale Institutional Review Board approved the study protocol and waived the need for informed consent as the study involves analyzing pre-existing data. Patients who opted out of research studies were not included in the study. Participants from ELSA-Brasil and the UKB provided informed consent, and their de-identified data were analyzed in this study.

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The data from the Yale New Haven Health System represent protected health information. To protect patient privacy, the Yale Institutional Review Board does not allow sharing of these data. Data from the Brazilian Longitudinal Study of Adult Health and the UK Biobank are available for research to licensed users.