Dataset Information

Predictors and Prognostic Implications of Cardiac Arrhythmias in Patients Hospitalized for COVID-19.

ABSTRACT:

Background

Cardiac manifestation of COVID-19 has been reported during the COVID pandemic. The role of cardiac arrhythmias in COVID-19 is insufficiently understood. This study assesses the incidence of cardiac arrhythmias and their prognostic implications in hospitalized COVID-19-patients.

Methods

A total of 166 patients from eight centers who were hospitalized for COVID-19 from 03/2020-06/2020 were included. Medical records were systematically analyzed for baseline characteristics, biomarkers, cardiac arrhythmias and clinical outcome parameters related to the index hospitalization. Predisposing risk factors for arrhythmias were identified. Furthermore, the influence of arrhythmia on the course of disease and related outcomes was assessed using univariate and multiple regression analyses.

Results

Arrhythmias were detected in 20.5% of patients. Atrial fibrillation was the most common arrhythmia. Age and cardiovascular disease were predictors for new-onset arrhythmia. Arrhythmia was associated with a pronounced increase in cardiac biomarkers, prolonged hospitalization, and admission to intensive- or intermediate-care-units, mechanical ventilation and in-hospital mortality. In multiple regression analyses, incident arrhythmia was strongly associated with duration of hospitalization and mechanical ventilation. Cardiovascular disease was associated with increased mortality.

Conclusions

Arrhythmia was the most common cardiac event in association with hospitalization for COVID-19. Older age and cardiovascular disease predisposed for arrhythmia during hospitalization. Whereas in-hospital mortality is affected by underlying cardiovascular conditions, arrhythmia during hospitalization for COVID-19 is independently associated with prolonged hospitalization and mechanical ventilation. Thus, incident arrhythmia may indicate a patient subgroup at risk for a severe course of disease.

SUBMITTER: Zylla MM

PROVIDER: S-EPMC7796041 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Publications

Predictors and Prognostic Implications of Cardiac Arrhythmias in Patients Hospitalized for COVID-19.

Zylla Maura M MM Merle Uta U Vey Johannes A JA Korosoglou Grigorios G Hofmann Eva E Müller Michael M Herth Felix F Schmidt Werner W Blessing Erwin E Göggelmann Christoph C Weidner Norbert N Fiedler Mascha O MO Weigand Markus A MA Kälble Florian F Morath Christian C Leiner Johannes J Kieser Meinhard M Katus Hugo A HA Thomas Dierk D

Journal of clinical medicine 20210102 1

<h4>Background</h4>Cardiac manifestation of COVID-19 has been reported during the COVID pandemic. The role of cardiac arrhythmias in COVID-19 is insufficiently understood. This study assesses the incidence of cardiac arrhythmias and their prognostic implications in hospitalized COVID-19-patients.<h4>Methods</h4>A total of 166 patients from eight centers who were hospitalized for COVID-19 from 03/2020-06/2020 were included. Medical records were systematically analyzed for baseline characteristics ...[more]

PMID: 33401735

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Project description:Atrial arrhythmias (AA) are common in hospitalized COVID-19 patients with limited data on their association with COVID-19 infection, clinical and imaging outcomes. In the related research article using retrospective research data from one quaternary care and five community hospitals, patients aged 18 years and above with positive SARS-CoV-2 polymerase chain reaction test were included. 6927 patients met the inclusion criteria. The data in this article provides demographics, home medications, in-hospital events and COVID-19 treatments, multivariable generalized linear regression regression models using a log link with a Poisson distribution (multi-parameter regression [MPR]) to determine predictors of new-onset AA and mortality in COVID-19 patients, computerized tomography chest scan findings, echocardiographic findings, and International Classification of Diseases-Tenth Revision codes. The clinical outcomes were compared to a propensity-matched cohort of influenza patients. For influenza, data is reported on baseline demographics, comorbid conditions, and in-hospital events. Generalized linear regression models were built for COVID-19 patients using demographic characteristics, comorbid conditions, and presenting labs which were significantly different between the groups, and hypoxia in the emergency room. Statistical analysis was performed using R programming language (version 4, ggplot2 package). Multivariable generalized linear regression model showed that, relative to normal sinus rhythm, history of AA (adjusted relative risk [RR]: 1.38; 95% CI: 1.11-1.71; p = 0.003) and newly-detected AA (adjusted RR: 2.02 95% CI: 1.68-2.43; p < 0.001) were independently associated with higher in-hospital mortality. Age in increments of 10 years, male sex, White race, prior history of coronary artery disease, congestive heart failure, end-stage renal disease, presenting leukocytosis, hypermagnesemia, and hypomagnesemia were found to be independent predictors of new-onset AA in the MPR model. The dataset reported is related to the research article entitled "Incidence, Mortality, and Imaging Outcomes of Atrial Arrhythmias in COVID-19" [Jehangir et al. Incidence, Mortality, and Imaging Outcomes of Atrial Arrhythmias in COVID-19, American Journal of Cardiology] [1].

Dataset Information

Predictors and Prognostic Implications of Cardiac Arrhythmias in Patients Hospitalized for COVID-19.

Background

Methods

Results

Conclusions

Publications

Predictors and Prognostic Implications of Cardiac Arrhythmias in Patients Hospitalized for COVID-19.

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