Year: 2025
Type: article
Study design: Observational Study
Abstract: Aim: Coronavirus disease 2019 (COVID-19) has been linked to various arrhythmias, including atrial and ventricular ectopy, atrial fibrillation, and conduction disturbances.Proposed mechanisms include myocardial injury, systemic inflammation, autonomic dysfunction, and endothelial damage.This study aimed to assess arrhythmic burden and its predictors in patients with prior COVID-19 infection using 24-hour Holter monitoring. Materials and Methods:We retrospectively analyzed 153 patients who underwent Holter electrocardiography (ECG) between January 2021 and June 2023.Participants were divided into COVID-19 positive (n=62) and control (n=91) groups.Demographic, clinical, and laboratory characteristics were compared.Ventricular ectopic beats (VES) were quantified, and ROC analysis identified 571 VES/day as the threshold for high arrhythmic burden.Patients were stratified accordingly, and predictors of high burden were determined using multivariate logistic regression.Results: VES counts were significantly higher in the COVID positive group (p<0.001).Patients with >571 VES had a higher frequency of fragmented QRS (75.0% vs. 7.6%) and prior COVID-19 infection (60.4% vs. 31.4%)(p<0.001 for both).In multivariate analysis, fragmented QRS [odds ratio (OR): 26.99, p<0.001] and COVID-19 history (OR: 10.30, p<0.001) independently predicted high arrhythmic burden.COVID-19 vaccination was associated with a reduced risk (OR: 0.13, p=0.006).Conclusion: COVID-19 infection is significantly associated with increased ventricular ectopy and fragmented QRS on Holter ECG, indicating persistent arrhythmic risk.Fragmented QRS and COVID-19 history independently predict high arrhythmic burden, while vaccination appears protective.Post-COVID rhythm surveillance may help identify high-risk individuals.
Source: Namık Kemal Tıp Dergisi
Institutions: Trakya University, University of Patras
Language: English
Subfield: Cardiology and Cardiovascular Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4414912690
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