Artificial intelligence in cardiovascular medicine: systematic review of randomised controlled trials

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ID: 332172
2026
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Abstract
Abstract Background Artificial intelligence (AI) holds considerable promise for improving cardiovascular care, but prior to widespread adoption AI-powered tools require evaluation in randomised trials. We systematically reviewed the current evidence from randomised trials of AI tools in cardiovascular medicine. Methods We conducted a systematic review of randomised trials comparing AI tools vs. standard care in cardiovascular medicine. PubMed, the Cochrane Central Register of Controlled Trials, Scopus, and the International Clinical Trials Registry Platform were searched from January 1, 2018, to April 10, 2026. Screening and full-text review were performed by three independent reviewers and risk of bias was assessed using the RoB 2 criteria. Results Of 11,151 identified records, 8,599 remained after removal of duplicates. Following screening and full-text review, 25 trials met the eligibility criteria. These trials evaluated AI tools in acute cardiovascular care (n = 3), cardiac imaging (n = 6), decision support for medical therapy (n = 6), electrophysiology (n = 8), and interventional cardiology (n = 2). Nine trials were single-centre, and two were international. Seventeen trials (68%) reported positive results, defined by non-inferiority or superiority of the AI-based strategy. Overall risk of bias was rated as high or with some concerns in 84% of the included trials, and only 36% explicitly reported following the CONSORT-/SPIRIT-AI reporting guidelines. Discussion Evidence from randomised trials evaluating AI tools in cardiovascular medicine is limited and most trials have a high risk of bias. Wider implementation of AI tools into practice requires robust, international, multi-centre randomised trials that evaluate patient-relevant outcomes, ensure external validity, and adhere to reporting guidelines. Trial registration number: PROSPERO CRD420251019264
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Authors Michael Kunz, Tiffany Péquignot, Tobias Zimmermann, Ivo Strebel, Wayne Zeng, Sven Knecht, Julia Andrea Freiermuth, Arnaud Champetier, Koray Durak, Dimitrios Doudesis, Kuan Ken Lee, Andrew Chapman, Gregor Leibundgut, Felix Mahfoud, Gary S. Collins, Richard D Riley, Nicholas L. Mills, Christian Eugen Mueller, Pedro López‐Ayala, Jasper Boeddinghaus
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Journal European Heart Journal - Digital Health
Year 2026
DOI
10.1093/ehjdh/ztag164
URL
https://doi.org/10.1093/ehjdh/ztag164
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