Original Research ArticleInternational Journal of Research in Medical Sciences
Publication: Electrocardiographic findings in COVID-19 patients
Int J Res Med Sci. 2021;9(2):378-385.DOI10.18203/2320-6012.ijrms20210410
Abstract
Background Severe acute respiratory syndrome coronavirus 2 (SARS CoV2) has caused the global pandemic, COVID-19. Though predominantly a respiratory illness, cardiac manifestations of COVID-19 significantly contribute to mortality. We wanted to determine whether admission electrocardiographic (ECG) characteristics provide prognostic information in COVID-19.
Methods We performed a retrospective, cross-sectional observational study in a designated District COVID hospital. COVID-19 patient’s medical records were converted into an electronic database which included demographic data, clinical characteristics and electrocardiogram recorded at/near the time of admission. Primary outcome assessed was the occurrence of severe COVID-19.
Results Of 180 patients, the majority were males (67.8%) and aged 31-50 years (38.9%). The predominant comorbidity among patients who were discharged (non-severe COVID-19 disease) and those who got referred (severe COVID-19 disease) was hypertension (56.5% vs 43.3%), followed by diabetes mellitus (37.7% vs 36.7%). Fatigue (41.9%) and cough (18.5%) were the most frequent symptoms among non-severe cases. Of 32.8% of the patients with abnormal ECG, abnormal axis (25.5%), poor R wave progression (23.5%), T inversion (15.3%), left ventricular hypertrophy (12.2%) followed by ST segment depression (8.3%) were the frequent findings. Logistic regression analysis revealed that elderly patients (>60 years) (β=2.276, OR=9.737, p=0.002), Heart rate (β=0.191, OR=1.211, p=0.045) and ST segment depression (β=9.986, OR=21725.39, p=0.022) showed statistically significant positive association with Severe COVID-19.
Conclusions ST segment abnormalities on admission ECG are markers of cardiac injury and may assist in prognostication of COVID-19. Early identification of these findings might play a crucial role in identifying patients likely to progress to severe COVID-19.
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Affiliations
- Department of General Medicine, Gayatri Vidya Parishad Institute of Healthcare and Medical Technology, Visakhapatnam, Andhra Pradesh, India
- Department of General Medicine, Government Medical College, Srikakulam, Andhra Pradesh, India
