Objectives: A significant proportion of COVID-19 patients may have cardiac involvement including arrhythmias. Although arrhythmia characterization and possible predictors were previously reported, there are conflicting data regarding the exact prevalence of arrhythmias. Clinically applicable algorithms to classify COVID patients’ arrhythmic risk are still lacking, and are the aim of our study. Methods: We describe a single center cohort of hospitalized patients with a positive nasopharyngeal swab for COVID-19 during the initial Israeli outbreak between 1/2/2020 –30/5/2020. The study’s outcome was any documented arrhythmia during hospitalization, based on daily physical examination, routine ECG’s, periodic 24-hour Holter, and continuous monitoring. Multivariate analysis was used to find predictors for new arrhythmias and create classification trees for discriminating patients with high and low arrhythmic risk. Results: Out of 390 COVID-19 patients included, 28 (7.2%) had documented arrhythmias during hospitalization, including: 23 atrial tachyarrhythmias, combined atrial fibrillation (AF) and ventricular fibrillation, ventricular tachycardia storm, and 3 bradyarrhythmias. Only 7/28 patients had previous arrhythmias. Our study showed significant correlation between disease severity and arrhythmia prevalence (p<0.001) with a low arrhythmic prevalence among mild disease patients (2%). Multivariate analysis revealed background heart failure (CHF) and disease severity are independently associated with overall arrhythmia while age, CHF, disease severity, and arrhythmic symptoms are associated with tachyarrhythmias. A novel decision tree using age, disease severity, CHF, and troponin levels was created to stratify patients into high and low risk for developing arrhythmia. Conclusions: Dominant arrhythmia among COVID-19 patients is AF. Arrhythmia prevalence is dependent on age, disease severity, CHF, and troponin levels. A novel simple Classification tree, based on these parameters, can discriminate between high and low arrhythmic risk patients.

Background: The liberal administration of hydroxychloroquine-sulphate (HCQ) to COVID-19 patients has raised concern regarding the risk of QTc prolongation and cardiac arrhythmias, particularly when prescribed with azithromycin. We evaluated the incidence of QTc prolongation among moderately and severely ill COVID-19 patients treated with HCQ and of the existence of concomitant alternative causes. Methods: All COVID-19 patients treated with HCQ (between Mar 1 and Apr 14, 2020) in a tertiary medical center were included. Clinical characteristics and relevant risk factors were collected from the electronic medical records. Individual patient QTc intervals were determined before and after treatment with HCQ. The primary outcome measure sought was a composite endpoint comprised of either an increase ≥ 60 milliseconds (ms) in the QTc interval compared with pretreatment QTc, and/or a maximal QTc interval >500 ms. Results: Ninety patients were included. Median age was 65 years (IQR 55-75) and 57 (63%) were male. Thirty-nine patients (43%) were severely or critically ill. Hypertension and obesity were common (n=23 each, 26%). QTc prolongation evolved in fourteen patients (16%). Age > 65 years, congestive heart failure, severity of disease, C-reactive protein level, hypokalemia and furosemide treatment, were all associated with QTc prolongation. Adjusted analysis showed that QTc prolongation was five times more likely with hypokalemia [OR 5, (95% CI, 1.3-20)], and three times more likely with furosemide treatment [OR 3 (95% CI, 1.01-13.7)]. Conclusion: In patients treated with HCQ, QTc prolongation was associated with the presence of traditional risk factors such as hypokalemia and furosemide treatment.