Surface electrocardiographic characteristics in coronavirus disease 2019: repolarization abnormalities associated with cardiac involvement

Chen, Liang; Feng, Yi; Tang, Jia; Hu, Wei; Zhao, Ping; Guo, Xiaoxiao; Huang, Ninghao; Gu, Yuwei; Hu, Linjie; Duru, Firat; Xiong, Chenglong; Chen, Mingquan

AIMS: The coronavirus disease 2019 (COVID‐19) has spread rapidly around the globe, causing significant morbidity and mortality. This study aims to describe electrocardiographic (ECG) characteristics of COVID‐19 patients and to identify ECG parameters that are associated with cardiac involvement. METHODS AND RESULTS: The study included patients who were hospitalized with COVID‐19 diagnosis and had cardiac biomarker assessments and simultaneous 12‐lead surface ECGs. Sixty‐three hospitalized patients (median 53 [inter‐quartile range, 43–65] years, 76.2% male) were enrolled, including patients with (n = 23) and without (n = 40) cardiac injury. Patients with cardiac injury were older, had more pre‐existing co‐morbidities, and had higher mortality than those without cardiac injury. They also had prolonged QTc intervals and more T wave changes. Logistic regression model identified that the number of abnormal T waves (odds ratio (OR), 2.36 [95% confidence interval (CI), 1.38–4.04], P = 0.002) and QTc interval (OR, 1.31 [95% CI, 1.03–1.66], P = 0.027) were independent indicators for cardiac injury. The combination model of these two parameters along with age could well discriminate cardiac injury (area the under curve 0.881, P < 0.001) by receiver operating characteristic analysis. Cox regression model identified that the presence of T wave changes was an independent predictor of mortality (hazard ratio, 3.57 [1.40, 9.11], P = 0.008) after adjustment for age. CONCLUSIONS: In COVID‐19 patients, presence of cardiac injury at admission is associated with poor clinical outcomes. Repolarization abnormalities on surface ECG such as abnormal T waves and prolonged QTc intervals are more common in patients with cardiac involvement and can help in further risk stratification.