Sociodemographic and clinical characteristics of hospital admissions for COVID-19: A retrospective cohort of patients in two hospitals in the south of Brazil

Author:

Jesus Edna Ribeiro deORCID,Boell Julia Estela Willrich,Reckziegel Juliana Cristina Lessmann,Vaz Rafael Sittoni,Goulart Marco Aurélio,Peluso Flávia Marin,Nogueira Tiago da Cruz,Ávila Márcio Costa Silveira de,Malkiewiez Michelle Mariah,Schmidt Catiele RaquelORCID,Weissenberg Vanessa Cruz Corrêa,Piccolin Millena Maria,Charão Junior Walmiro Martins,Lorenzini ElisianeORCID

Abstract

Background This database aims to present the sociodemographic and clinical profile of a cohort of 799 patients hospitalized with coronavirus disease 2019 (COVID-19) in two hospitals in southern Brazil. Methods Data were collected, retrospectively, from November 2020 to January 2021, from the medical records of all hospital admissions that occurred from 1 April 2020 to 31 December 2020. The analysis of these data can contribute to the definition of the clinical and sociodemographic profile of patients with COVID-19. Data description This dataset covers 799 patients hospitalized for COVID-19, characterized by the following sociodemographic variables: sex, age group, race, marital status and paid work. The sex variable was collected as sex assigned at birth from medical records data. Clinical variables included: admission to clinical ward, hospitalization in the Intensive Care Unit, COVID-19 diagnosis, number of times hospitalized due to COVID, hospitalization time in days and risk classification protocol. Other clinical variables include: pulmonary impairment; patients ventilation pattern; high-flow oxygen mask; pulmonary thromboembolism; cardiovascular disease; pulmonary sepsis; influenza exam results. Other health problems: diabetes, systemic arterial hypertension, chronic obstructive pulmonary disease, obesity, tabaco smoking, asthma, chronic kidney disease, overweight, vascular accident, sedentary lifestyle, HIV/AIDS, cancer, Alzheimer's disease, Parkinson's disease. Conclusions The analysis of these data can contribute to the definition of the clinical and sociodemographic profile of patients with COVID-19. Thus, a great social impact is demonstrated when databases are published. Open data accelerates the research process, facilitates reuse and enriches datasets, in addition to optimizing the application of public resources, that is, enabling more use of the same investment.

Funder

The project is funded by the Foundation for Research Support of Santa Catarina

Publisher

F1000 Research Ltd

Subject

General Pharmacology, Toxicology and Pharmaceutics,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine

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