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Data of atrial arrhythmias in hospitalized COVID-19 and influenza patients
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 1...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9008092/ https://www.ncbi.nlm.nih.gov/pubmed/35449710 http://dx.doi.org/10.1016/j.dib.2022.108177 |
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author | Jehangir, Qasim Lee, Yi Latack, Katie Poisson, Laila Wang, Dee Dee Song, Shiyi Apala, Dinesh R. Patel, Kiritkumar Halabi, Abdul R. Krishnamoorthy, Geetha Sule, Anupam A. |
author_facet | Jehangir, Qasim Lee, Yi Latack, Katie Poisson, Laila Wang, Dee Dee Song, Shiyi Apala, Dinesh R. Patel, Kiritkumar Halabi, Abdul R. Krishnamoorthy, Geetha Sule, Anupam A. |
author_sort | Jehangir, Qasim |
collection | PubMed |
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]. |
format | Online Article Text |
id | pubmed-9008092 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-90080922022-04-14 Data of atrial arrhythmias in hospitalized COVID-19 and influenza patients Jehangir, Qasim Lee, Yi Latack, Katie Poisson, Laila Wang, Dee Dee Song, Shiyi Apala, Dinesh R. Patel, Kiritkumar Halabi, Abdul R. Krishnamoorthy, Geetha Sule, Anupam A. Data Brief Data Article 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]. Elsevier 2022-04-14 /pmc/articles/PMC9008092/ /pubmed/35449710 http://dx.doi.org/10.1016/j.dib.2022.108177 Text en © 2022 The Author(s). Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Jehangir, Qasim Lee, Yi Latack, Katie Poisson, Laila Wang, Dee Dee Song, Shiyi Apala, Dinesh R. Patel, Kiritkumar Halabi, Abdul R. Krishnamoorthy, Geetha Sule, Anupam A. Data of atrial arrhythmias in hospitalized COVID-19 and influenza patients |
title | Data of atrial arrhythmias in hospitalized COVID-19 and influenza patients |
title_full | Data of atrial arrhythmias in hospitalized COVID-19 and influenza patients |
title_fullStr | Data of atrial arrhythmias in hospitalized COVID-19 and influenza patients |
title_full_unstemmed | Data of atrial arrhythmias in hospitalized COVID-19 and influenza patients |
title_short | Data of atrial arrhythmias in hospitalized COVID-19 and influenza patients |
title_sort | data of atrial arrhythmias in hospitalized covid-19 and influenza patients |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9008092/ https://www.ncbi.nlm.nih.gov/pubmed/35449710 http://dx.doi.org/10.1016/j.dib.2022.108177 |
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