Erroneous Computer Electrocardiogram Interpretation of Atrial Fibrillation and Its Clinical Consequences

Abstract

Background: The aim of this study was to determine the frequency and nature of errors made by computer electrocardiogram (ECG) analysis of atrial fibrillation (AF), and the clinical consequences. Hypothesis: Computer software for interpreting ECGs has advanced. Methods: A total of 10279 ECGs were collected, automatically interpreted by the built-in ECG software, and then reread by 2 cardiologists. AF-related ECGs were classified into 3 groups: overinterpreted AF (rhythms other than AF interpreted as AF), misinterpreted AF (AF interpreted as rhythms other than AF), and true AF (AF interpreted as AF by both computer ECG interpretation and cardiologists).Results: There were 1057 AF-related ECGs from 409 patients. Among these, 840 ECGs (79.5%) were true AF. Overinterpretation occurred in 98 (9.3%) cases. Sinus rhythm and sinus tachycardia with premature atrial contraction and/or baseline artifact and sinus arrhythmia were commonly overinterpreted as AF. Heart rate ≤60 bpm and baseline artifact significantly increased the likelihood of overinterpreted AF. Misdiagnosis occurred in 119 (11.3%) cases, in which AF was usually misdiagnosed as sinus or supraventricular tachycardia. The presence of tachycardia and low-amplitude atrial activity significantly increased the likelihood of misdiagnosis of AF. Among the erroneous computer ECG interpretations, 17 cases (7.8%) were not corrected by the ordering physicians and/or repeat computer-ECG interpretation; inappropriate follow-up studies or treatments of the patients were undertaken with no serious sequelae. Conclusions: Erroneous computer ECG interpretation of AF was not rare. Attention should be concentrated on educating physicians about ECG appearance and confounding factors of AF, along with ongoing quality control of built-in software for automatic ECG interpretation.

Computerized electrocardiography in healthy conscious guinea pigs (Cavia porcellus)

“…However, this exam has certain limitations with inappropriate arrhythmia diagnosis due to built-in software. Reports describe 7.8% of error in clinical cases, especially when events of atrial fibrillation occur (Bae et al 2012). Therefore preliminary software interpretations require reading and confirmation by a qualified eletrocardiographer (Estes 2013).…”

Rhythmic chaos: irregularities of computer ECG diagnosis

“…Box 2 shows the common differentials for atrial fibrillation that are reported on ECG. (10,11) In conclusion, the ECG, like all other investigations, should always be interpreted in relation to the patient and the clinical scenarios. The computer is not, and should not be, a surrogate for a physician's knowledge and clinical acumen but, when utilised appropriately, can certainly be a useful aid in clinical management.…”

Big Data and Artificial Intelligence: Opportunities and Threats in Electrophysiology

“…Data-driven Versus Hypothesis-driven Research pacemaker artefacts, comorbidities affecting the ECG or medication affecting the rhythm or conduction, might influence the performance of DNNs. [13][14][15][16][17][18] Instead of true disease characteristics, ECG changes due to clinical interventions are used by the DNN to classify ECGs. For example, a DNN using chest X-rays provided insight into long-term mortality, but the presence of a thoracic drain and inadequately labelled input data resulted in an algorithm that was unsuitable for clinical decision-making.…”