eMurmur ID – Clinical Performance Evaluation

Overview

The differentiation between innocent and pathologic murmurs through traditional auscultation can often be challenging, which in the end makes the diagnosis strongly dependent on the clinitians experience and clinical expertise. With the development of technology it is now possible to help diagnose heart murmurs using computer aided auscultation systems (CAA). eMurmur ID is an investigational CAA system (not FDA cleared) and the investigators hypothesize that it can distinguish between AHA class I (pathologic murmurs) and AHA class III heart sounds (innocent murmurs and/or no murmurs) with a sensitivity and specificity not worse compared to a similar FDA cleared CAA system on market.

Full Title of Study: “eMurmur ID – Clinical Performance Evaluation”

Study Type

  • Study Type: Observational [Patient Registry]
  • Study Design
    • Time Perspective: Cross-Sectional
  • Study Primary Completion Date: April 24, 2018

Interventions

  • Device: Automated Heart Murmur Detection AI
    • Automated AI algorithm-based analysis of digital heart sound recordings to detect and classify heart murmurs. Heart sound recordings were fully blinded before undergoing one-time automated analysis. AI algorithm results for each recording include: AHA classification (Class I (pathologic heart murmur) versus class III (innocent heart murmur or no heart murmur), murmur timing, murmur grade, heart rate and S1/S2 identification.

Clinical Trial Outcome Measures

Primary Measures

  • eMurmur ID sensitivity and specificity
    • Time Frame: 1 day
    • The primary endpoints of the study are sensitivity and specificity. The clinical reference gold standard diagnosis is defined as expert physicians’ diagnosis confirmed by independently interpreted echocardiogram diagnosis. True positive (TP), true negative (TN), false positive (FP) and false negative (FN) will be determined via comparison of the heart murmur classification results with the clinical gold standard (echocardiogram) diagnosis.

Participating in This Clinical Trial

Inclusion Criteria

  • All age groups of patients will be included from 1day old – Patients who are being followed for known congenital heart disease and are returning for follow up – Patients referred for a suspected heart murmur Exclusion Criteria:

  • Mismatch between the expert physician's diagnosis (auscultation based) and the diagnosis resulting from echocardiography (independently read by a cardiologist blinded to the auscultation results). Note: both, the expert physician and echocardiography results must independently reach the same diagnosis, which is then accepted as the gold standard reference diagnosis to which both devices are compared to. This is necessary because not every pathology visible on an echocardiogram causes an audible murmur, and not every murmur heard by a medical expert might correlate to pathology. – Patient whose behaviour does not allow for a standard auscultation by the physician (e.g. a screaming fit).

Gender Eligibility: All

Minimum Age: 1 Day

Maximum Age: N/A

Are Healthy Volunteers Accepted: Accepts Healthy Volunteers

Investigator Details

  • Lead Sponsor
    • CSD Labs GmbH
  • Provider of Information About this Clinical Study
    • Sponsor
  • Overall Official(s)
    • Lillian Lai, MD, Principal Investigator, Children’s Hopsital of Eastern Ontario, Canada

References

Lai LS, Redington AN, Reinisch AJ, Unterberger MJ, Schriefl AJ. Computerized Automatic Diagnosis of Innocent and Pathologic Murmurs in Pediatrics: A Pilot Study. Congenit Heart Dis. 2016 Sep;11(5):386-395. doi: 10.1111/chd.12328. Epub 2016 Mar 15.

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