Literature DB >> 18257026

The impact of computer-assisted auscultation on physician referrals of asymptomatic patients with heart murmurs.

Raymond L Watrous1, W Reid Thompson, Stacey J Ackerman.   

Abstract

BACKGROUND: As many as 50-70% of asymptomatic children referred for specialist evaluation or echocardiography because of a murmur have no heart disease. HYPOTHESIS: Computer-assisted auscultation (CAA) can improve the sensitivity and specificity of referrals for evaluation of heart murmurs.
METHODS: Seven board-certified primary care physicians were evaluated both without and with use of a computer-based decision-support system using 100 prerecorded patient heart sounds (55 innocent murmurs, 30 pathological murmurs, 15 without murmur). The sensitivity and specificity of their murmur referral decisions relative to American College of Cardiology/American Heart Association (ACC/AHA) guidelines, and sensitivity and specificity of murmur detection and characterization (innocent versus pathological) were measured.
RESULTS: Sensitivity for detection of murmurs significantly increased with use of CAA from 76.6 to 89.1% (p <0.001), while specificity remained unaffected (80.0 versus 81.0%). Computer-assisted auscultation improved sensitivity of correctly identifying pathological murmur cases from 82.4 to 90.0%, and specificity of correctly identifying benign cases (with innocent or no murmurs) from 74.9 to 88.8%. (p <0.001). Referral sensitivity increased from 86.7 to 92.9%, while specificity increased from 63.5 to 78.6% using CAA (p <0.001).
CONCLUSIONS: Computer-assisted auscultation appears to be a promising new technology for informing the referral decisions of primary care physicians. Copyright (c) 2008 Wiley Periodicals, Inc.

Entities:  

Mesh:

Year:  2008        PMID: 18257026      PMCID: PMC6653399          DOI: 10.1002/clc.20185

Source DB:  PubMed          Journal:  Clin Cardiol        ISSN: 0160-9289            Impact factor:   2.882


  11 in total

1.  An Intelligent Phonocardiography for Automated Screening of Pediatric Heart Diseases.

Authors:  Amir A Sepehri; Armen Kocharian; Azin Janani; Arash Gharehbaghi
Journal:  J Med Syst       Date:  2015-10-30       Impact factor: 4.460

2.  Initial Field Test of a Cloud-Based Cardiac Auscultation System to Determine Murmur Etiology in Rural China.

Authors:  Lee Pyles; Pouya Hemmati; J Pan; Xiaoju Yu; Ke Liu; Jing Wang; Andreas Tsakistos; Bistra Zheleva; Weiguang Shao; Quan Ni
Journal:  Pediatr Cardiol       Date:  2017-02-02       Impact factor: 1.655

3.  In defence of auscultation: a glorious future?

Authors:  W Reid Thompson
Journal:  Heart Asia       Date:  2017-02-01

4.  Multi-center, multi-topic heart sound databases and their applications.

Authors:  Meilan Xie; Shouzhong Xiao; Tianhu Liu; Qijian Yi; Fengzhi You; Xingming Guo; Yong Shao; Junmimg Huo; Deqi Du; Dongmei Xu; Wenzhu Wu; Zifu Xiao; Yong Yang; Weizhen Guo
Journal:  J Med Syst       Date:  2010-02-23       Impact factor: 4.460

Review 5.  Biomedical informatics for computer-aided decision support systems: a survey.

Authors:  Ashwin Belle; Mark A Kon; Kayvan Najarian
Journal:  ScientificWorldJournal       Date:  2013-02-04

Review 6.  The promise of computer-assisted auscultation in screening for structural heart disease and clinical teaching.

Authors:  L Zühlke; L Myer; B M Mayosi
Journal:  Cardiovasc J Afr       Date:  2012-02-23       Impact factor: 1.167

7.  Estimating pressure gradients by auscultation: How technology (echocardiography) can help improve clinical skills.

Authors:  Rohini L Kadle; Colin K L Phoon
Journal:  World J Cardiol       Date:  2017-08-26

8.  The Diagnostic Utility of Computer-Assisted Auscultation for the Early Detection of Cardiac Murmurs of Structural Origin in the Periodic Health Evaluation.

Authors:  Pierre L Viviers; Jo-Anne H Kirby; Jeandré T Viljoen; Wayne Derman
Journal:  Sports Health       Date:  2017-02-01       Impact factor: 3.843

9.  A Framework for AI-Assisted Detection of Patent Ductus Arteriosus from Neonatal Phonocardiogram.

Authors:  Sergi Gómez-Quintana; Christoph E Schwarz; Ihor Shelevytsky; Victoriya Shelevytska; Oksana Semenova; Andreea Factor; Emanuel Popovici; Andriy Temko
Journal:  Healthcare (Basel)       Date:  2021-02-05

10.  Efficiency, sensitivity and specificity of automated auscultation diagnosis device for detection and discrimination of cardiac murmurs in children.

Authors:  Armen Kocharian; Amir-Ahmad Sepehri; Azin Janani; Elaheh Malakan-Rad
Journal:  Iran J Pediatr       Date:  2013-08       Impact factor: 0.364

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.