Literature DB >> 23185081

Evaluation of cardiac auscultation skills in pediatric residents.

Komal Kumar1, W Reid Thompson.   

Abstract

UNLABELLED: Auscultation skills are in decline, but few studies have shown which specific aspects are most difficult for trainees. We evaluated individual aspects of cardiac auscultation among pediatric residents using recorded heart sounds to determine which elements pose the most difficulty.
METHODS: Auscultation proficiency was assessed among 34 trainees following a pediatric cardiology rotation using an open-set format evaluation module, similar to the actual clinical auscultation description process.
RESULTS: Diagnostic accuracy for distinguishing normal from abnormal cases was 73%. Findings most commonly correctly identified included pathological systolic and diastolic murmurs and widely split second heart sounds. Those least likely to be identified included continuous murmurs and clicks. Accuracy was low for identifying specific diagnoses.
CONCLUSIONS: Given time constraints for clinical skills teaching, this suggests that focusing on distinguishing normal from abnormal heart sounds and murmurs instead of making specific diagnoses may be a more realistic goal for pediatric resident auscultation training.

Entities:  

Mesh:

Year:  2012        PMID: 23185081     DOI: 10.1177/0009922812466584

Source DB:  PubMed          Journal:  Clin Pediatr (Phila)        ISSN: 0009-9228            Impact factor:   1.168


  11 in total

1.  In defence of auscultation: a glorious future?

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

2.  Developing Physical Exam Skills in Residency: Comparing the Perspectives of Residents and Faculty About Values, Barriers, and Teaching Methods.

Authors:  John W Ragsdale; Catherine Habashy; Sarita Warrier
Journal:  J Med Educ Curric Dev       Date:  2020-11-26

3.  Virtual auscultation course via video chat in times of COVID-19 improves cardiac auscultation skills compared to literature self-study in third-year medical students: a prospective randomized controlled cross-over study.

Authors:  Nils Rüllmann; Raphael Hirtz; Unaa Lee; Kathrin Klein; Ertan Mayatepek; Bastian Malzkorn; Carsten Döing
Journal:  GMS J Med Educ       Date:  2022-04-14

4.  Cardiac auscultation via simulation: a survey of the approach of UK medical schools.

Authors:  Samantha Jayne Owen; Kenneth Wong
Journal:  BMC Res Notes       Date:  2015-09-10

5.  Automatic recognition of murmurs of ventricular septal defect using convolutional recurrent neural networks with temporal attentive pooling.

Authors:  Jou-Kou Wang; Yun-Fan Chang; Kun-Hsi Tsai; Wei-Chien Wang; Chang-Yen Tsai; Chui-Hsuan Cheng; Yu Tsao
Journal:  Sci Rep       Date:  2020-12-11       Impact factor: 4.379

6.  Small Steps in Impacting Clinical Auscultation of Medical Students.

Authors:  Edem K Binka; Linda O Lewin; Peter R Gaskin
Journal:  Glob Pediatr Health       Date:  2016-09-15

Review 7.  Artificial intelligence-aided decision support in paediatrics clinical diagnosis: development and future prospects.

Authors:  Yawen Li; Tiannan Zhang; Yushan Yang; Yuchen Gao
Journal:  J Int Med Res       Date:  2020-09       Impact factor: 1.671

8.  Cardiac Auscultation Lab Using a Heart Sounds Auscultation Simulation Manikin.

Authors:  Antonia Quinn; Jennifer Kaminsky; Andrew Adler; Shirley Eisner; Robin Ovitsh
Journal:  MedEdPORTAL       Date:  2019-10-18

9.  The Simulated Cardiology Clinic: A Standardized Patient Exercise Supporting Medical Students' Biomedical Knowledge and Clinical Skills Integration.

Authors:  Jennifer M Jackson; R Brandon Stacey; Sharon S Korczyk; Donna M Williams
Journal:  MedEdPORTAL       Date:  2020-10-28

10.  The Effect of Signal Duration on the Classification of Heart Sounds: A Deep Learning Approach.

Authors:  Xinqi Bao; Yujia Xu; Ernest Nlandu Kamavuako
Journal:  Sensors (Basel)       Date:  2022-03-15       Impact factor: 3.576

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