NCT03227848

eMurmur ID - Clinical Performance Evaluation

• Status: Completed
• Phase: —
• Study type: Observational
• Enrollment: 120 (actual)
• Sponsor: CSD Labs GmbH · Academic / Other
• Sex: All
• Age: 1 Day
• Healthy volunteers: Accepted

Summary

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.

Conditions

• Heart Murmurs
• Pathologic Murmurs
• Innocent Murmurs
• Congenital Heart Defect
• Systolic Murmurs
• Diastolic Murmurs

Interventions

Type	Name	Description
DEVICE	Automated Heart Murmur Detection AI	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.

Timeline

• Start date: 2017-01-04
• Primary completion: 2018-04-24
• Completion: 2018-04-30
• First posted: 2017-07-24
• Last updated: 2018-07-18

Locations

1 site across 1 country: Canada

Regulatory

• FDA-regulated device study