Brief Title
Automated Phonocardiography Analysis in Adults
Official Title
Phonokardiographie Bei Erwachsenen
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.
Study Type
Observational
Primary Outcome
Sensitivity for pathological heart murmur detection
Condition
Aortic Insufficiency
Intervention
Automated Heart Murmur Detection AI
Publications
* Includes publications given by the data provider as well as publications identified by National Clinical Trials Identifier (NCT ID) in Medline.
Recruitment Information
Recruitment Status
Device
Estimated Enrollment
90
Start Date
December 10, 2015
Completion Date
January 31, 2017
Primary Completion Date
January 18, 2017
Eligibility Criteria
Inclusion Criteria: - Adults with a heart defect verified by echocardiography
Gender
All
Ages
18 Years - N/A
Accepts Healthy Volunteers
No
Contacts
Rita Riedlbauer, MD, ,
Location Countries
Austria
Location Countries
Austria
Administrative Informations
NCT ID
NCT03600051
Organization ID
GRZ03 (PbE)
Responsible Party
Sponsor
Study Sponsor
CSD Labs GmbH
Study Sponsor
Rita Riedlbauer, MD, Principal Investigator, Medical University of Graz
Verification Date
July 2018