Clinical trial NCT02512341: Automatic Differentiation of Innocent and Pathologic Murmurs in Pediatrics
Official title: Automatic Differentiation of Innocent and Pathologic Murmurs in Pediatrics
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Heart Murmurs
Mitral Valve Prolapse
Systolic Murmurs
Keywords: Computer Aided Auscultation (CAA)
Electronic Stethoscope
Phonocardiography
Heart Auscultation
Lead sponsor: CSD Labs GmbH
Sponsor class: OTHER
First posted: 2015-07-30
Enrollment: 106
Sex: ALL
Maximum age (years): 18
Standard ages: CHILD
ADULT
Accepts healthy volunteers: yes
Observational model: COHORT
Time perspective: CROSS_SECTIONAL
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.

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.

Detailed description: Background:

Computer aided auscultation in the differentiation of pathologic (AHA class I) from no- or innocent murmurs (AHA class III) would be of great value to the general practitioner and potentially also to the specialist. This would allow objective screening for structural heart disease, standardized documentation of auscultation findings, and may avoid unnecessary referrals to pediatric cardiologists. Our goal was to further develop and assess the quality of a novel computational algorithm that automatically classifies murmurs of phonocardiograms (PCGs) acquired in a pediatric population.

Methods:

Patients with no-, innocent-, and pathologic murmurs were recruited from the general pediatric cardiology clinic. Using an electronic stethoscope, PCGs were acquired by the pediatric cardiologist from each patient. The PCGs were analyzed by the algorithm and diagnoses were compared to findings by the pediatric specialist and echocardiography as the gold standard.

The following registry procedures and quality factors have been implemented in this preliminary clinical study:

* Quality assurance plan, including

  * data validation
  * proper registration procedures
* Source data verification to assess the accuracy, completeness, or representativeness of registry data by comparing the data to external data sources (medical records and paper case report forms).
* Standard Operating Procedures to address registry operations and analysis activities, including patient recruitment, data collection, data management, data analysis.

Eligibility criteria: Inclusion Criteria:

* outpatient
* parental approval for study participation

Exclusion Criteria:

* none

Primary outcomes:
measure: Number of correctly diagnosed pathological heart murmurs through independent algorithm-based auscultation.
timeFrame: 2 months
Secondary outcomes:
measure: Number of correctly diagnosed pathological heart murmurs through traditional stethoscope based auscultation by medical experts.
timeFrame: 2 months
Other outcomes:
Locations:
city: Ottawa
country: Canada
facility: Children's Hospital of Eastern Ontario
Study officials:
affiliation: Children's Hospital of Eastern Ontario
name: Lillian Lai, MD
role: PRINCIPAL_INVESTIGATOR
References: