Randomized Controlled Trials Evaluating Artificial Intelligence in Cardiovascular Care

Abstract

BACKGROUND: Artificial intelligence (AI) has shown promise in transforming health care, particularly in cardiology. However, there is a lack of high-quality evidence demonstrating its impact on crucial clinical outcomes. OBJECTIVES: The purpose of this study was to synthesize existing evidence from randomized controlled trials (RCTs) on the application of AI in cardiology, evaluating its impact on key clinical outcomes. METHODS: We conducted a systematic review following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, searching MEDLINE, Web of Science, and the Cochrane Library from inception to November 2024. We included RCTs evaluating machine learning models compared to traditional methods in cardiovascular care. Primary outcomes focused on patient-important metrics, while secondary outcomes covered time and resource savings. RESULTS: Eleven RCTs met the inclusion criteria. Studies were conducted between 2021 and 2024, with 81.2% being multicenter trials. Five studies (45.5%) reported improvements in clinical events, 6 (54.5%) showed enhanced diagnostic accuracy and early detection, and 3 (27.3%) demonstrated improved resource utilization. CONCLUSIONS: This review highlights AI's potential to enhance cardiovascular care through improved early detection, diagnostic accuracy, and resource efficiency. However, the limited number of RCTs indicates a need for more high-quality studies to validate AI's effectiveness across various clinical domains.

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