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

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.

Predictors of Deaths Associated With Covid-19 in Patients Admitted to Two Hospitals in the State of Santa Catarina, Brazil

“…However, regarding missing information characterization, there was a random pattern (Missing completely at random, MCAR), i.e., there were missing data that did not impact the observed effects. The database is available for reuse 38 . Other issues that may 13/17…”

Preditores De Óbitos Associados À Covid-19 Em Pacientes Internados Em Dois Hospitais Do Estado De Santa Catarina, Brasil

“…O banco de dados completo do estudo encontra-se publicado no repositório Figshare Dataset da Springer Nature, repositório específico de acesso público (https://doi.org/10.6084/ m9.figshare.16746073.v3) 12 .…”