Abstract
Objective: Intelligent electronic stethoscopes and computer-aided auscultation systems have highlighted a new era in cardiac auscultation in children. Several collaborative multidisciplinary researches in this field are performed by physicians and computer specialists. Recently, a novel medical software device, Automated Auscultation Diagnosis Device (AADD), has been reported with intelligent diagnosing ability to differentiate cardiac murmur from breath sounds in children with normal and abnormal hearts due to congenital heart disease. The aim of this study is to determine efficiency, sensitivity and specificity of the diagnoses made by this AADD in children with and without cardiac disease.
Methods: We performed a cross-sectional study to determine efficiency, sensitivity and specificity of diagnoses made by AADD. Our patient population was two groups of children with and without cardiac disease(563 patients and 50 normal). SPSS version 16 was used to calculate sensitivity, specificity and efficiency and descriptive analysis.
Findings: Using cardiac sound recording in four conventional cardiac areas of auscultation (including aortic, pulmonary, tricuspid and mitral), AADD proved to have a ≥90 % sensitivity, specificity and efficiency for making the correct diagnosis in children with heart disease and 100% diagnostic accuracy in children with normal hearts either with or without innocent murmurs.
Conclusion: Considering the high sensitivity, specificity and efficiency of AADD for making the correct diagnosis, application of this software is recommended for family physicians to enhance proper and timely patients’ referral to pediatric cardiologists in order to provide better diagnostic facilities for pediatric patients who live in deprived and underserved rural areas with lack access to pediatric cardiologists.
Keywords
Computerized Medical Records System Computer-Assisted Diagnosis Computer-Assisted Design Auscultation
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Copyright
© 2013, Author(s). This open-access article is available under the Creative Commons Attribution 4.0 (CC BY 4.0) International License (https://creativecommons.org/licenses/by/4.0/), which allows for unrestricted use, distribution, and reproduction in any medium, provided that the original work is properly cited.