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.
Study Type
OBSERVATIONAL
Enrollment
120
Automated AI algorithm-based analysis of digital heart sound recordings to detect and classify heart murmurs. Heart sound recordings were fully blinded before undergoing one-time automated analysis. AI algorithm results for each recording include: AHA classification (Class I (pathologic heart murmur) versus class III (innocent heart murmur or no heart murmur), murmur timing, murmur grade, heart rate and S1/S2 identification.
Children's Hospital of Eastern Ontario
Ottawa, Canada
eMurmur ID sensitivity and specificity
The primary endpoints of the study are sensitivity and specificity. The clinical reference gold standard diagnosis is defined as expert physicians' diagnosis confirmed by independently interpreted echocardiogram diagnosis. True positive (TP), true negative (TN), false positive (FP) and false negative (FN) will be determined via comparison of the heart murmur classification results with the clinical gold standard (echocardiogram) diagnosis.
Time frame: 1 day
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