Surface electrocardiographic characteristics in coronavirus disease 2019: repolarization abnormalities associated with cardiac involvement.
ESC Heart Fail
; 7(6): 4408-4415, 2020 Dec.
Article
in English
| MEDLINE | ID: covidwho-746384
ABSTRACT
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 ANDRESULTS:
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.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Type of study:
Prognostic study
Language:
English
Journal:
ESC Heart Fail
Year:
2020
Document Type:
Article
Affiliation country:
Ehf2.12991
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