Automatic Differentiation of Innocent and Pathologic Murmurs in Pediatrics

NCT02512341 | Completed

• 1 other identifier: OTT01
• Study Type: observational
• Target: 106
• Locations: 1 country
• Sites: 1

Brief Summary

The purpose of this preliminary clinical study is to assess the quality of a computational algorithm that automatically classifies murmurs of phonocardiograms (PCGs) as either pathologic (AHA class I) or as no- or innocent (AHA class III) in the pediatric population. Each patient is auscultated and diagnosed independently by a medical specialist by means of a standard mechanical stethoscope. Additionally, for each patient, a PCG is recorded using a Littmann 3200 electronic stethoscope and later analyzed using the computational algorithm. An echocardiogram is performed as the gold-standard for determining heart pathologies. The results of the computer aided auscultation (CAA) are compared to the findings of the medical professionals as well as to the echocardiogram findings. Hypothesis: The specific CAA algorithms used in this study are able to differentiate pathologic (AHA class I) from no- or innocent murmurs (AHA class III) in a pediatric population.

Conditions

Heart Murmurs; Mitral Valve Prolapse; Systolic Murmurs

Keywords

Computer Aided Auscultation (CAA); Electronic Stethoscope; Phonocardiography; Heart Auscultation

Outcome Measures

Primary Outcomes (1)

• Number of correctly diagnosed pathological heart murmurs through independent algorithm-based auscultation.

  Each patient is screened and diagnosed regarding a potential heart murmur by a medical expert through standard stethoscope-based auscultation. Heart sounds are recorded using an electronic Littmann 3200 stethoscope. The resulting phonocardiograms are analyzed and diagnosed independently, offline, with no external input, by an algorithm. A final diagnosis for each patient is made by a medical expert by performing an echocardiogram, the gold standard method for heart murmur detection. The diagnoses of both the medical expert and the algorithm are finally compared to the echocardiogram-based diagnosis.

  2 months

Secondary Outcomes (1)

• Number of correctly diagnosed pathological heart murmurs through traditional stethoscope based auscultation by medical experts.

  2 months

Interventions

Computer Aided Auscultation (CAA) DEVICE

Also known as: Phonocardiogram analysis, Automated heart murmur classification, Murmur screening

Eligibility Criteria

• Age: Up to 18 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Child (0-17), Adult (18-64)
• Sampling Method: Non-Probability Sample

Study Population

Outpatients with and without heart defects showing pathological heart murmurs, innocent heart murmurs and heart sounds without murmurs at the cardiology department.

You may qualify if:

• outpatient
• parental approval for study participation

You may not qualify if:

• none

Sponsors & Collaborators

• CSD Labs GmbH: lead

Study Sites (1)

Children's Hospital of Eastern Ontario

Ottawa, Canada

Location

MeSH Terms

Conditions

Heart Murmurs; Mitral Valve Prolapse; Systolic Murmurs

Condition Hierarchy (Ancestors)

Signs and Symptoms; Pathological Conditions, Signs and Symptoms; Heart Valve Prolapse; Heart Valve Diseases; Heart Diseases; Cardiovascular Diseases

Study Officials

• Lillian Lai, MD

  Children's Hospital of Eastern Ontario

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: CROSS SECTIONAL
• Target Duration: 1 Day
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: July 29, 2015
• First Posted: July 30, 2015
• Study Start: November 1, 2013
• Primary Completion: December 1, 2013
• Study Completion: June 1, 2014
• Last Updated: July 18, 2018

Record last verified: 2018-07

Locations

CA (1)