View clinical trials related to Innocent Murmurs.
Filter by:The purpose of this research is to prospectively test and validate the utility of Eko artificial intelligence (AI) plus Eko Murmur Analysis Software (EMAS) murmur characterization in algorithm in a real world, point-of-care setting.
The purpose of this research is to evaluate the impact of Eko AI plus EMAS (Eko Murmur Analysis Software) on a clinician's referral decision in a real-world primary care setting. There is an additional objective of understanding patient outcomes when patients are referred for cardiology follow-up and/or echocardiogram.
The Eko CORE and DUO stethoscopes are FDA-approved electronic devices that have the capacity to record heart sounds. The study seeks to expand murmur detection to include VHD classification through the development of novel ML algorithms that are able to distinguish between systolic vs. diastolic vs. continuous murmurs, as well as classify VHD type and severity, using 4-point auscultation with Eko CORE and DUO electronic stethoscopes to record heart sounds.
The differentiation between innocent and pathologic murmurs through traditional auscultation can often be challenging, which in the end makes the diagnosis strongly dependent on the clinitians experience and clinical expertise. With the development of technology it is now possible to help diagnose heart murmurs using computer aided auscultation systems (CAA). eMurmur ID is an investigational CAA system (not FDA cleared) and the investigators hypothesize that it can distinguish between AHA class I (pathologic murmurs) and AHA class III heart sounds (innocent murmurs and/or no murmurs) with a sensitivity and specificity not worse compared to a similar FDA cleared CAA system on market.