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Efficiency, Sensitivity and Specificity of Automated Auscultation Diagnosis Device for Detection and Discrimination of Cardiac Murmurs in Children

机译:儿童心脏杂音的自动听诊诊断装置的效率,灵敏度和特异性

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ObjectiveIntelligent 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.MethodsWe 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.FindingsUsing 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.ConclusionConsidering 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.
机译:客观智能的电子听诊器和计算机辅助听诊系统突显了儿童心脏听诊的新时代。医师和计算机专家在该领域进行了几项合作的多学科研究。近来,已经报道了一种新颖的医疗软件设备,即自动听诊诊断设备(AADD),具有智能诊断能力,可将先天性心脏病导致的正常和异常心脏患儿的心脏杂音与呼吸音区分开。这项研究的目的是确定该AADD对有或没有心脏病的儿童进行诊断的效率,敏感性和特异性。方法我们进行了一项横断面研究,以确定AADD对诊断的有效性,敏感性和特异性。我们的患者人群为两组患有和不患有心脏病的儿童(563名患者和50名正常儿童)。 SPSS 16版用于计算敏感性,特异性和有效性以及描述性分析。发现在四个常规听诊心脏区域(包括主动脉,肺,三尖瓣和二尖瓣)使用心音记录,AADD被证明具有≥90%的敏感性,特异性和对患有心脏病的儿童进行正确诊断的效率较高,对有或没有无杂音的正常心脏的儿童具有100%的诊断准确性。结论考虑到AADD的高敏感性,特异性和高效率,可以进行正确的诊断,建议使用此软件家庭医生应加强适当和及时的患者转诊给儿科心脏病专家,以便为生活在贫困且服务不足的农村地区而无法获得儿科心脏病专家的儿科患者提供更好的诊断工具。

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