Publication details

Data analysis of diagnostic accuracies in 12-lead electrocardiogram interpretation by junior medical fellows


NOVOTNÝ Tomáš BOND Raymond Robert ANDRŠOVÁ Irena KOC Lumír ŠIŠÁKOVÁ Martina FINLAY Dewar Darren GULDENRING Daniel ŠPINAR Jindřich MALIK Marek

Year of publication 2015
Type Article in Periodical
Magazine / Source Journal of Electrocardiology
MU Faculty or unit

Faculty of Medicine

Field Cardiovascular diseases incl. cardiosurgery
Keywords Diagnostic accuracy; Electrocardiogram interpretation; Fellows; Training
Description 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.

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