Maya E Guglin1, Neeta Datwani. 1. Wayne State University/John D. Dingell VAMC, Department of Medicine, Section of Cardiology, Detroit, MI 48201, USA. meguglin@prodigy.net
Abstract
OBJECTIVE: We analyzed the accuracy with which a computer algorithm reads electrocardiograms (ECGs) with electronic pacemakers (PMs). METHODS: Electrocardiograms were screened for the presence of electronic pacing spikes. Computer-derived interpretations were compared with cardiologists' readings. RESULTS: Computer-drawn interpretations required revision by cardiologists in 61.3% of cases. In 18.4% of cases, the ECG reading algorithm failed to recognize the presence of a PM. The misinterpretation of paced beats as intrinsic beats led to multiple secondary errors, including myocardial infarctions in varying localization. The most common error in computer reading was the failure to identify an underlying rhythm. This error caused frequent misidentification of the PM type, especially when the presence of normal sinus rhythm was not recognized in a tracing with a DDD PM tracking the atrial activity. CONCLUSION: The increasing number of pacing devices, and the resulting number of ECGs with pacing spikes, mandates the refining of ECG reading algorithms. Improvement is especially needed in the recognition of the underlying rhythm, pacing spikes, and mode of pacing.
OBJECTIVE: We analyzed the accuracy with which a computer algorithm reads electrocardiograms (ECGs) with electronic pacemakers (PMs). METHODS: Electrocardiograms were screened for the presence of electronic pacing spikes. Computer-derived interpretations were compared with cardiologists' readings. RESULTS: Computer-drawn interpretations required revision by cardiologists in 61.3% of cases. In 18.4% of cases, the ECG reading algorithm failed to recognize the presence of a PM. The misinterpretation of paced beats as intrinsic beats led to multiple secondary errors, including myocardial infarctions in varying localization. The most common error in computer reading was the failure to identify an underlying rhythm. This error caused frequent misidentification of the PM type, especially when the presence of normal sinus rhythm was not recognized in a tracing with a DDD PM tracking the atrial activity. CONCLUSION: The increasing number of pacing devices, and the resulting number of ECGs with pacing spikes, mandates the refining of ECG reading algorithms. Improvement is especially needed in the recognition of the underlying rhythm, pacing spikes, and mode of pacing.