Improvement of an Algorithm to Detect Structural Heart Murmurs in Adult Patients Using Electronic Stethoscopes
Trial Parameters
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Brief Summary
The main objective of this study is to evaluate a machine learning model's ability to detect murmurs indicative of structural heart disease ("structural murmur") by analyzing phonocardiogram waveforms-and simultaneous electrocardiogram waveforms when available-in multiple auscultatory positions per subject. Diagnosis of structural murmur will be confirmed by gold-standard echocardiography and reviewed by an expert panel of cardiologists.
Eligibility Criteria
Inclusion Criteria: * 18+ years old * Patient or patient's legal healthcare proxy consents to participation * Documented history of SHD * Undergoing (or has undergone, within 30 days) a complete echocardiogram * Willing to have heart recordings done with two different electronic stethoscopes Exclusion Criteria: * Patient or proxy is unwilling/unable to give written informed consent * Unable to complete a complete echocardiogram, or none recent completed within the last 30 days * No documented history of SHD * Experiencing a known or suspected acute cardiac event * Mechanical ventricular support (such as ECMO, LVAD, RVAD, BiVAD, Impella, intra-aortic balloon pumps, TAH, VentrAssist, DuraHeart, HVAD, EVAHEART LVAS, HeartMate, Jarvik 2000) * Unwilling or unable to follow or complete study procedures