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

Ethical approval and consent to participate

This research was approved by the Research Ethics Committee of the Federal University of Santa Catarina (UFSC), (opinion No. 4.323.917/2020) Santa Catarina, Brazil. Patients provided written informed consent for data collection and publication.

Research design and method of data collection

This database comes from a cohort of patients who were admitted with a diagnosis of COVID-19 in two hospitals in southern Brazil. Retrospectively, from November 2020 to January 2021, data were collected from medical records of all hospital admissions that occurred from 1 April 2020 to 31 December 2020. Data related to the sex of the patients refer to the biological characteristics at birth from the patients’ medical records. All patients aged 18 years or older were included. This dataset covers 799 hospitalized patients.

Questionnaires hosted in the Survey Monkey platform were used, which contained questions about sociodemographic data, health conditions, and clinical, therapeutic, and outcome data. The variables considered for this study were: sex, age, age group, race, marital status, years of education, number of hospitalizations, hospitalization units, length of hospitalizations, risk classification, whether a COVID-19 test was taken, test used to detect COVID-19, respiratory compromise, ventilatory pattern, evolution, and previous diseases.

The inclusion criteria were: hospital admissions with a medical diagnosis of COVID-19; and being 18 years old or older. Individuals under 18 years of age and those who were not hospitalized due to COVID-19 were excluded.

Data description

Data were characterized by the following variables: sex, age group, race, marital status and paid work. The following clinical variables are included: admission to clinical ward, hospitalization in the Intensive Care Unit (ICU), COVID-19 diagnosis, number of times hospitalized by COVID, hospitalization time in days and risk classification protocol (green, yellow, red and not informed), the classification was defined in the protocol according to Manchester Triage System.^17,18 Other clinical variables included: pulmonary impairment according to medical diagnosis based on lung tomography evaluation: <50%, between 50 and 75% or >75%; patients ventilation pattern (presented dyspnea with respiratory effort, dyspnea without effort or without dyspnea); high-flow oxygen mask; pulmonary thromboembolism (PE); cardiovascular disease; pulmonary sepsis (according to medical diagnosis of pulmonary sepsis); influenza exam results. Other health problems (if yes or no): diabetes, systemic arterial hypertension, chronic obstructive pulmonary disease (COPD), obesity, tabaco smoking, asthma, chronic kidney disease, overweight, vascular accident (Stroke), sedentary lifestyle, human immunodeficiency virus (HIV/AIDS), cancer, Alzheimer's disease, Parkinson's disease. The description of these characteristics is provided in Table 1. The analysis and reuse of sociodemographic and clinical profile data can be performed using descriptive statistics and measures of central tendency (mean and median) and variability (standard deviation and interquartile range), as well as absolute and relative distributions (n-%). The symmetry of the continuous distribution can be assessed using the Kolmogorov-Smirnov test. The predictive power of the variables can be analyzed using logistic regression. The opening of data from research projects is one of the most important elements of the research lifecycle for the success of Open Science. This is a sine qua non for reproducibility and scientific progress. Open Data speeds up the research process, facilitates reuse and enriches data sets, in addition to optimizing the application of public resources, in other words, enabling more use of the same investment. Opening data also allows detecting false, biased and inaccurate conclusions, as they are subject to replicability tests. Thus, great social impact is demonstrated when databases are published.¹⁹

Dataset validation

Limitations

This dataset is limited to a retrospective cohort of patients from two hospitals in southern Brazil. This can be considered a limitation. The variables regarding the pulmonary condition, such as sepsis and pulmonary involvement, ended up being defined by the medical group, through a medical report of tomography and clinical medical diagnosis of pulmonary sepsis, which could be seen as a limitation in the study. However, the data are very relevant, as there are few published studies and databases available on COVID-19 in Brazil. Researchers interested in the sociodemographic and clinical profile of patients hospitalized for COVID-19 can extensively explore the variables described here.

Ethical considerations

The present study was approved by the Research Ethics Committee of the Federal University of Santa Catarina (UFSC), (opinion No. 4.323.917/2020) Santa Catarina, Brazil. The basis and necessary information about the study objectives and method were given to all participants before the commencement of the study, and written informed consent was obtained from them. Participants consented to data publication. Participants were assured of the confidentiality of data and that only general statistics would be presented.