Evaluating the frequency of false-positive detection in electrocardiogram devices in comparison to cardiologist diagnosis: instrument validation study (Preprint)

Abstract

Electrocardiography is the most convenient and cost-effective method at the primary level of healthcare infrastructure to localize and diagnose Myocardial infarction, ischemic heart diseases, and numerous arrhythmias. The manufacturers of ECG machines provide computer-generated Interpretations. However, these machines have differences in implementing the algorithms, which causes a change in diagnostic accuracy. Hence, the occurrence of False positives is the most commonly observed error that occurs during computer interpretation.

This study aims to evaluate the differences observed in the computerized interpretation of ECG reports regarding the Cardiologist's diagnosis.

The 12-lead ECG reports were collected from a 12-lead gold standard machine and a smartphone-based 12 lead ECG machine. The data of the 294 subjects out of 300 subjects were accessed from both ECG machines. The reports were evaluated by a Cardiologist based on the observational changes in the morphology of the ECG traces.

The gold standard ECG machine was 92% sensitive, 47.9% specific and 26.43% accurate in correctly interpreting a normal ECG report concerning the diagnosis provided by a Cardiologist. Whereas the Smartphone-based 12 lead ECG was found to be 95.9% sensitive, 88.9% specific, and 86.2% accurate in detecting a normal ECG concerning the diagnosis provided by a Cardiologist.

The ECG machine manufacturer's interpretation algorithm plays an important role in defining the accuracy of the ECG machine. Computerized interpretation is only an assisting tool for clinicians and not an independent tool to be relied on while treating a patient during health emergencies and check-ups.