Automated Phonocardiography Analysis in Adults

Completed

• Conditions: Aortic Insufficiency; Aortic Stenosis; Insufficiency, Pulmonary; Mitral Insufficiency; Tricuspid Regurgitation; Mitral Insufficiency and Aortic Stenosis; Insufficiency, Tricuspid

• Registration Number: NCT03600051
• Lead Sponsor: CSD Labs GmbH

Brief Summary

Background: Computer aided auscultation in the differentiation of pathologic (AHA class I) from no- or innocent murmurs (AHA class III) via artificial intelligence algorithms could be a useful tool to assist healthcare providers in identifying pathological heart murmurs and may avoid unnecessary referrals to medical specialists.

Objective: Assess the quality of the artificial intelligence (AI) algorithm that autonomously detects and classifies heart murmurs as either pathologic (AHA class I) or as no- or innocent (AHA class III).

Hypothesis: The algorithm used in this study is able to analyze and identify pathologic heart murmurs (AHA class I) in an adult population with valve defects with a similar sensitivity compared to medical specialist.

Methods: Each patient is auscultated and diagnosed independently by a medical specialist by means of standard auscultation. Auscultation findings are verified via gold-standard echocardiogram diagnosis. For each patient, a phonocardiogram (PCG) - a digital recording of the heart sounds - is acquired. The recordings are later analyzed using the AI algorithm. The algorithm results are compared to the findings of the medical professionals as well as to the echocardiogram findings.

Detailed Description

Not available

Study Timeline

• Study Start: 2015-12-10
• Primary Completion: 2017-01-18
• Study Completion: 2017-01-31
• Status Verified: 2018-07
• Study First Submitted: 2018-07-16
• Study First Submitted QC: 2018-07-16
• Last Update Submitted: 2018-07-16
• Study First Posted: 2018-07-26
• Last Update Posted: 2018-07-26

Recruitment & Eligibility

• Status: COMPLETED
• Sex: All
• Target Recruitment: 90

Inclusion Criteria

• Adults with a heart defect verified by echocardiography

Exclusion Criteria

Not provided

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Sensitivity for pathological heart murmur detection	2 months	Ability to detect a pathological heart murmur in digital heart sound recordings obtained from an elderly population with heart valve disease.

Trial Locations

Locations (1)

University Hospital; 🇦🇹 Graz, Styria, Austria