Automated Phonocardiography Analysis in Adults

July 16, 2018 updated by: CSD Labs GmbH

Phonokardiographie Bei Erwachsenen

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 Overview

Study Type

Observational

Enrollment (Actual)

90

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

    • Styria
      • Graz, Styria, Austria, 8010
        • University Hospital

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Sampling Method

Non-Probability Sample

Study Population

Elderly in-patient subjects admitted to the Division of Cardiology, University Hospital Graz, Austria. All patients had known pathological murmurs caused by multiple valve defects, confirmed by gold standard echocardiography. Defects were interpreted by the cardiologist as "low, medium or high" severity. Altogether, 155 valve defects were observed, including insufficiencies of the aortic, mitral, tricuspid, and pulmonary valves; and stenosis of the aortic and mitral valves.

Description

Inclusion Criteria:

  • Adults with a heart defect verified by echocardiography

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Sensitivity for pathological heart murmur detection
Time Frame: 2 months
Ability to detect a pathological heart murmur in digital heart sound recordings obtained from an elderly population with heart valve disease.
2 months

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Investigators

  • Principal Investigator: Rita Riedlbauer, MD, Medical University of Graz

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

December 10, 2015

Primary Completion (Actual)

January 18, 2017

Study Completion (Actual)

January 31, 2017

Study Registration Dates

First Submitted

July 16, 2018

First Submitted That Met QC Criteria

July 16, 2018

First Posted (Actual)

July 26, 2018

Study Record Updates

Last Update Posted (Actual)

July 26, 2018

Last Update Submitted That Met QC Criteria

July 16, 2018

Last Verified

July 1, 2018

More Information

Terms related to this study

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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