title: Computerized Automatic Diagnosis of Innocent and Pathologic Murmurs in Pediatrics: A Pilot Study.
abstract: OBJECTIVE
  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. 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 assess the quality of a novel computerized algorithm that automatically classifies murmurs in phonocardiograms (PCGs) acquired in a pediatric population.
  
  
  METHODS
  This is a pilot study testing the ability of a novel computerized algorithm to accurately diagnose PCGs compared with interpreted echocardiograms as a gold standard.
  
  
  METHODS
  This study was performed in pediatric cardiology clinics at a tertiary care hospital.
  
  
  METHODS
  All incoming patients were recruited, including patients with no murmurs, innocent murmurs, and pathologic murmurs (106 patients).
  
  
  METHODS
  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 with findings by echocardiograms interpreted by pediatric cardiologists which were used as the gold standard.
  
  
  METHODS
  Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were calculated.
  
  
  RESULTS
  When compared with echocardiography as a gold standard in diagnosing murmurs, the computerized algorithm tested on N=34 PCGs, yielded a sensitivity of 87% and specificity of 100%, a positive predictive value of 100%, negative predictive value of 90% and an accuracy of 94%.
  
  
  CONCLUSIONS
  With echocardiogram as a gold standard, this computerized algorithm can detect pathologic murmurs with high sensitivity, specificity and accuracy, comparable to if not better than published results of pediatric cardiologists and neonatologists. This study confirms the high quality and "real-world" robustness of a novel computational algorithm in the assessment of pediatric murmurs.
authors.affiliation: Children's Hospital of Eastern Ontario, University of Ottawa, Ottawa, Ontario, Canada. llai@cheo.on.ca.
authors.forename: Lillian S W
authors.initials: LS
authors.lastname: Lai
authors.affiliation: The Heart Institute, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA.
authors.forename: Andrew N
authors.initials: AN
authors.lastname: Redington
authors.affiliation: CSD Labs GmbH, Graz, Austria.
authors.forename: Andreas J
authors.initials: AJ
authors.lastname: Reinisch
authors.affiliation: CSD Labs GmbH, Graz, Austria.
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Unterberger
authors.affiliation: CSD Labs GmbH, Graz, Austria.
authors.forename: Andreas J
authors.initials: AJ
authors.lastname: Schriefl
mesh_terms: D000293:Adolescent; D000465:Algorithms; D002648:Child; D002675:Child, Preschool; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D003937:Diagnosis, Differential; D004452:Echocardiography / Q000379:methods*; D005260:Female; D005500:Follow-Up Studies; D006337:Heart Murmurs / Q000175:diagnosis*; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D010865:Pilot Projects; D011237:Predictive Value of Tests; D012372:ROC Curve; D012016:Reference Values; D012189:Retrospective Studies; D019023:Stethoscopes
keywords: Auscultation; Automatic Detection; Cardiology; Computerized Assisted Auscultation; Consultation; Echocardiogram; Elective; Medical Software; Murmur; Pediatric