Journal of electrocardiology · 2025
Diagnostic accuracy of atrial fibrillation by computerized electrocardiogram analysis versus cardiologist interpretation.
СтатьяСравнительное исследованиеНазвание и аннотация: Перевод в очереди
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Escabí-Mendoza José, Rivera-Guzmán Norwin, Rivera-Babilonia Jaime, Martínez-Díaz Jorge, Cochran-Pérez María R, Rodríguez-Santiago Jonathan X, Jovet-Toledo Gerardo, Engel-Rodriguez Andrew
Аннотация
BACKGROUND: Advancements in computerized electrocardiogram (ECG) interpretation have improved efficiency, but concerns remain regarding diagnostic accuracy for atrial fibrillation (AF). Misclassification may result in inappropriate treatment and adverse outcomes.
OBJECTIVES: To compare the diagnostic accuracy of computerized ECG interpretation versus cardiologist over-read for AF and evaluate the clinical consequences of diagnostic errors.
METHODS: We conducted a retrospective study of 5000 ECGs obtained at the Veterans Affairs Caribbean Healthcare System between September and November 2017. All ECGs were initially interpreted by automated software. A subset of 905 ECGs underwent over-read at the time of care. Separately, two board-certified cardiologists independently reviewed all 5000 ECGs in a blinded fashion and completed standardized interpretation forms. Diagnostic metrics were compared using 2-proportion z-tests and McNemar's test. Logistic regression identified predictors of misclassification. Clinical records were reviewed for treatment consequences.
RESULTS: Computerized interpretation identified 803 (16 %) AF-related ECGs; of these, 70 % were true AF, 11 % false positives, and 19 % false negatives. Cardiologist interpretation showed higher accuracy: sensitivity 87 % vs. 78 %, specificity 99 % vs. 97 %, PPV 98 % vs. 86 %, NPV 99 % vs. 97 % (all p < 0.01). Ventricular pacing (OR 10.2), undetermined rhythm (OR 13.4), and tachycardia (OR 1.8) independently predicted misclassification (p < 0.001). Among misclassified ECGs, 41 % of errors were unrecognized, leading to delayed anticoagulation (18 %), inappropriate initiation (12 %), and three adverse events.
CONCLUSIONS: Computerized ECG interpretation of AF is prone to diagnostic error. Cardiologist over-read improves accuracy and may reduce preventable harm.
CONDENSED ABSTRACT: Computerized ECG interpretation misclassified AF in 30 % of cases, 11 % overcalls and 19 % missed diagnoses. Cardiologist over-reading demonstrated superior accuracy (87 % sensitivity, 99 % specificity), minimizing both false positives and negatives. In 41 % of erroneous computer interpretations, providers failed to recognize the error, leading to delayed anticoagulation, inappropriate therapy, two thromboembolic events, and one bleeding-related hospitalization. Ventricular pacing, undetermined rhythms, and tachycardia were key predictors of misclassification. These findings highlight the limitations of automated ECG analysis and support structured cardiologist over-read to safeguard against diagnostic errors and improve patient outcomes in AF detection.
OBJECTIVES: To compare the diagnostic accuracy of computerized ECG interpretation versus cardiologist over-read for AF and evaluate the clinical consequences of diagnostic errors.
METHODS: We conducted a retrospective study of 5000 ECGs obtained at the Veterans Affairs Caribbean Healthcare System between September and November 2017. All ECGs were initially interpreted by automated software. A subset of 905 ECGs underwent over-read at the time of care. Separately, two board-certified cardiologists independently reviewed all 5000 ECGs in a blinded fashion and completed standardized interpretation forms. Diagnostic metrics were compared using 2-proportion z-tests and McNemar's test. Logistic regression identified predictors of misclassification. Clinical records were reviewed for treatment consequences.
RESULTS: Computerized interpretation identified 803 (16 %) AF-related ECGs; of these, 70 % were true AF, 11 % false positives, and 19 % false negatives. Cardiologist interpretation showed higher accuracy: sensitivity 87 % vs. 78 %, specificity 99 % vs. 97 %, PPV 98 % vs. 86 %, NPV 99 % vs. 97 % (all p < 0.01). Ventricular pacing (OR 10.2), undetermined rhythm (OR 13.4), and tachycardia (OR 1.8) independently predicted misclassification (p < 0.001). Among misclassified ECGs, 41 % of errors were unrecognized, leading to delayed anticoagulation (18 %), inappropriate initiation (12 %), and three adverse events.
CONCLUSIONS: Computerized ECG interpretation of AF is prone to diagnostic error. Cardiologist over-read improves accuracy and may reduce preventable harm.
CONDENSED ABSTRACT: Computerized ECG interpretation misclassified AF in 30 % of cases, 11 % overcalls and 19 % missed diagnoses. Cardiologist over-reading demonstrated superior accuracy (87 % sensitivity, 99 % specificity), minimizing both false positives and negatives. In 41 % of erroneous computer interpretations, providers failed to recognize the error, leading to delayed anticoagulation, inappropriate therapy, two thromboembolic events, and one bleeding-related hospitalization. Ventricular pacing, undetermined rhythms, and tachycardia were key predictors of misclassification. These findings highlight the limitations of automated ECG analysis and support structured cardiologist over-read to safeguard against diagnostic errors and improve patient outcomes in AF detection.