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@article{1321544,
author = {Novotný, Tomáš and Bond, Raymond Robert and Andršová, Irena and Koc, Lumír and Šišáková, Martina and Finlay, Dewar Darren and Guldenring, Daniel and Špinar, Jindřich and Malik, Marek},
article_location = {Philadelphia},
article_number = {6},
doi = {http://dx.doi.org/10.1016/j.jelectrocard.2015.08.023},
keywords = {Diagnostic accuracy; Electrocardiogram interpretation; Fellows; Training},
language = {eng},
issn = {0022-0736},
journal = {Journal of Electrocardiology},
title = {Data analysis of diagnostic accuracies in 12-lead electrocardiogram interpretation by junior medical fellows},
volume = {48},
year = {2015}
}
TY - JOUR
ID - 1321544
AU - Novotný, Tomáš - Bond, Raymond Robert - Andršová, Irena - Koc, Lumír - Šišáková, Martina - Finlay, Dewar Darren - Guldenring, Daniel - Špinar, Jindřich - Malik, Marek
PY - 2015
TI - Data analysis of diagnostic accuracies in 12-lead electrocardiogram interpretation by junior medical fellows
JF - Journal of Electrocardiology
VL - 48
IS - 6
SP - 988-994
EP - 988-994
PB - Churchill Livingstone Inc Medical Publishers
SN - 00220736
KW - Diagnostic accuracy
KW - Electrocardiogram interpretation
KW - Fellows
KW - Training
N2 - Background: The electrocardiogram (ECG) is the most commonly used diagnostic procedure for assessing the cardiovascular system. The aim of this study was to compare ECG diagnostic skill among fellows of cardiology and of other internal medicine specialties (non-cardiology fellows). Methods: A total of 2900 ECG interpretations were collected. A set of 100 clinical 12-lead ECG tracings were selected and classified into 12 diagnostic categories. The ECGs were evaluated by 15 cardiology fellows and of 14 non-cardiology fellows. Diagnostic interpretations were classified as (1) correct, (2) almost correct, (3) incorrect, and (4) dangerously incorrect. Multivariate logistic regression was used to assess confounding factors and to determine the odds ratios for the months of experience, age, sex, and the distinction between cardiology and non-cardiology fellows. Results: The mean rate of correct diagnoses by cardiology vs. non-cardiology fellows was 48.9 +/- 8.9% vs. 35.9 +/- 8.0% (p = 0.001; 70.1% vs. 55.0% for the aggregate of 'correct' and 'almost correct' diagnoses). There were 10.2 +/- 5.6% of interpretations classified as 'dangerously incorrect' by cardiology fellows vs. 16.3 +/- 5.0% by non-cardiology fellows (p = 0.008). The cardiology fellows achieved statistically significantly greater diagnostic accuracy in 7 out of the 12 diagnostic classes. In multivariable logistic regression, the distinction between cardiology and non-cardiology fellows was the only independent statistically significant (p < 0.001) predictor of whether the reader is likely correct or incorrect. Being a non-cardiology fellow reduced the probability of correct classification by 42% (odds ratio [95% confidence interval]: 0.58 [0.50; 0.68]). Conclusions: Although cardiology fellows out-performed the others, skills in ECG interpretation were found not adequately proficient. A comprehensive approach to ECG education is necessary. Further studies are needed to evaluate proper methods of training, testing, and continuous medical education in ECG interpretation.
ER -
NOVOTNÝ, Tomáš, Raymond Robert BOND, Irena ANDRŠOVÁ, Lumír KOC, Martina ŠIŠÁKOVÁ, Dewar Darren FINLAY, Daniel GULDENRING, Jindřich ŠPINAR and Marek MALIK. Data analysis of diagnostic accuracies in 12-lead electrocardiogram interpretation by junior medical fellows. \textit{Journal of Electrocardiology}. Philadelphia: Churchill Livingstone Inc Medical Publishers, 2015, vol.~48, No~6, p.~988-994. ISSN~0022-0736. Available from: https://dx.doi.org/10.1016/j.jelectrocard.2015.08.023.
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