Electrocardiographic abnormalities and troponin levels provide insight on the prognosis of COVID-19 patients: A single center experience from Iran

Coronavirus disease 2019 (COVID-19) is an infection which can present itself bythe involvement of various organs, but the most common manifestations are respiratorysymptoms, fever and dyspnea with a high mortality rate. In order to study the prognosis ofpatients and also to determine the treatment plan, we need non-invasive methods whichcan be easily used in the triage of patients. In this study, we investigated the diagnosticvalue of electrocardiographic (ECG) changes and troponin levels in patients with thisdisease. This is a descriptive study. Confirmed COVID-19 patients participated in thepresent study. Data were collected by taking history and referring to medical records. Weanalyzed data by using chi square, t test and logistic regression through SPSS softwareversion 22. One hundred and five patients with COVID-19 disease were examined. Mostpatients were men (53.3%) and the mean age was 54.53 years. The most common underlyingdiseases were hypertension and diabetes mellitus. Ninety-five patients had abnormalelectrocardiography including eleven with long QT; seven with arrhythmia; 78 with sinustachycardia; 7 with hemi-block; 1 with hemi-block and first degree atrioventricular block;4 with abnormal axis and 28 with ischemic changes. Eleven patients (10.5%) had positivetroponin level, whose length of hospital stay was higher (12.73 vs. 12.07 days). Furthermore,their mean length of intensive care unit (ICU) stay was also higher. In addition, among thetroponin-positive group, 100% had abnormal electrocardiography. The findings of the present study showed that ECG abnormalities and troponinlevels could provide good information about the prognosis of patients. Moreover, it seemsthat ECG changes in COVID-19 patients, whether indicative of underlying heart disease orresulted from infection, can affect the prognosis of patients. Therefore, considering ECGfindings and troponin levels can help select patients at a higher risk for triage.