[version 2; peer review: 1 approved, 1 approved with reservations]
No competing interests were disclosed.
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.
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.
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.
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.
Changes were made according to the reviewer's suggestion: risk classification protocol (green, yellow, red and not informed), the classification was defined in the protocol according to Manchester Triage System. Other clinical variables included: pulmonary impairment according to medical diagnosis based on lung tomography evaluation: <50%, between 50 and 75% or >75%.
The coronavirus disease 2019 (COVID-19) pandemic has been considered the greatest challenge of the present time, associated with the unprecedented crisis in the health area, due to the expressive demand for hospital beds by patients with severe coronavirus conditions, which resulted in the collapse of health systems worldwide.
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.
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 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.
| Label | Name of data file/data set | File types (file extension) | Data repository and identifier (DOI or accession number) |
|---|---|---|---|
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COVID-19 Hospital Admissions database | COVID-19 Hospital Admissions Database.xlsx |
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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.
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.
ERJ, EL and JEWB made substantial contributions to the conception and design of the work, or the acquisition, analysis or interpretation of data, and to the writing of the work or critically reviewing important intellectual content. They have given final approval to the version and have agreed to be responsible for all aspects of the work, ensuring that issues relating to the accuracy or completeness of any part of the work are properly investigated and resolved. JCRL, FMP, RSV, MAG, TCN, MCSA, MMP, MMM, CRS, WMCJ, VCCW, made substantial contributions to the acquisition of the data and the writing of the paper. They have approved the final version and agree to be responsible for all aspects of the work, ensuring that issues relating to the accuracy or completeness of any part of the work are properly investigated and resolved. All authors read and approved the final manuscript.
Figshare: Covid-19 Hospital Admissions Database.xlsx.
Data are available under the terms of the
This is an open access database distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution and reproduction, provided the original work is properly cited.
The authors gratefully acknowledge the Foundation for Research Support of Santa Catarina (FAPESC).
In response to the author's comments, a lingering uncertainty requiring clarification and refinement within the presented text persists. According to the information provided by the author, a sedentary lifestyle was defined as the absence of physical activity, and patients also reported that, in general, they do not engage in daily activities that increase the body's caloric expenditure. However, uncertainty remains regarding how this information was collected in cases of patients with moderate to severe conditions, such as those requiring oxygen or being intubated upon arrival at the hospital unit. Therefore, the proposal aims to elucidate the data collection procedures in order to ensure the reliability of the data.
Are sufficient details of methods and materials provided to allow replication by others?
Partly
Is the rationale for creating the dataset(s) clearly described?
Yes
Are the datasets clearly presented in a useable and accessible format?
Yes
Are the protocols appropriate and is the work technically sound?
Partly
Reviewer Expertise:
Research area in infectious and contagious diseases with a project similar to the one presented with the collection of information from patients hospitalized with COVID-19.
I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.
The authors have made the requested corrections.
Are sufficient details of methods and materials provided to allow replication by others?
Partly
Is the rationale for creating the dataset(s) clearly described?
Yes
Are the datasets clearly presented in a useable and accessible format?
Yes
Are the protocols appropriate and is the work technically sound?
Partly
Reviewer Expertise:
Research area in emergency and infectious. I participated in various studies about COVID-19 prognosis.
I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.
This article presents an open database to advance knowledge of the COVID-19 disease. It presents relative data from the beginning of the pandemic until the end of 2020, that is, in the first phase of this. It has been shown, as the authors indicate, that the lethality of this infection is marked by the age of the patients and their comorbidity.
Research design and data collection method
Inclusion criteria are appropriate The description of the variables is partially adequate. I think the age variable should be shown as a continuous and uncategorized variable. The authors should better describe some of the qualitative variables they present, and explain the categories that make them up. Among these variables that would have to be explained would be: risk classification protocol, pulmonary impairment and pulmonary sepsis.
Data description
Are sufficient details of methods and materials provided to allow replication by others?
Partly
Is the rationale for creating the dataset(s) clearly described?
Yes
Are the datasets clearly presented in a useable and accessible format?
Yes
Are the protocols appropriate and is the work technically sound?
Partly
Reviewer Expertise:
Research area in emergency and infectious. I participated in various studies about COVID-19 prognosis.
I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.
Inclusion criteria are appropriate
Data description
The description of the variables is partially adequate. I think the age variable should be shown as a continuous and uncategorized variable.
2Farrohknia N, Castrén M, Ehrenberg A, Lind L, Oredsson S, Jonsson H, et al. Emergency Department Triage Scales and their components: a systematic review of the scientific evidence. Scand J Trauma Resusc Emerg Med [Internet]. 2011 [cited 2023 Dec 8]; 19:42. Available from:
The information available can be accessed by researchers who are interested in better understanding health policies, planning health actions, and estimating costs and demands in emergency situations. Database studies of this nature are important as they contribute to improving the effectiveness of health promotion and prevention actions. The results of data analysis provide information to managers who can assess the situation and identify critical points and propose strategies in situations that require immediate solutions.
Review the inclusion and exclusion criteria. The author informs, “The inclusion criteria were: hospital admissions with a medical diagnosis of COVID-19; and be 18 years or older. Individuals under 18 years of age and those who were not hospitalized due to COVID-19 were excluded”, so if being 18 years of age or older is an inclusion criterion and hospital admissions with a medical diagnosis of COVID-19, the exclusion criteria must be those within this population who were included, not being 18 years old and being hospitalized for COVID-19 was already a characteristic or circumstance that prevented the inclusion of the subject in the study.
In the variables, the inclusion criterion is having a diagnosis of COVID-19 and being hospitalized, the diagnostic variable for COVID-19 is not justified since everyone in the study has this outcome. Inform how the risk classification (green, yellow, red and not informed) was defined in the protocol in the study patients. Is it relevant that the author informs the distinction between obesity and overweight, would it not be possible to present this information in a single variable? It is not clear in the text how the authors defined a sedentary lifestyle. It is suggested that age in the bank be presented as a continuous variable, which allows the application of numerous statistical methods with better power for inference and modeling. As the authors inform that they collected data regarding income, the information in the database would be interesting.
As argued by the authors, “open data streamline the research process, facilitate reuse and enrich datasets, in addition to optimizing the application of public resources, that is, enabling greater use of the same investment”, it would be recommended that the authors inform the geographical location of the two hospitals in southern Brazil, as well as better describing the population from which the sample originated.
I understand that this information described by the author “Researchers interested in the sociodemographic and clinical profile of patients hospitalized for COVID-19 can widely explore the variables described here”, is not a limitation.
Are sufficient details of methods and materials provided to allow replication by others?
Partly
Is the rationale for creating the dataset(s) clearly described?
Yes
Are the datasets clearly presented in a useable and accessible format?
Yes
Are the protocols appropriate and is the work technically sound?
Partly
Reviewer Expertise:
Research area in infectious and contagious diseases with a project similar to the one presented with the collection of information from patients hospitalized with COVID-19.
I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.
The information available can be accessed by researchers who are interested in better understanding health policies, planning health actions, and estimating costs and demands in emergency situations. Database studies of this nature are important as they contribute to improving the effectiveness of health promotion and prevention actions. The results of data analysis provide information to managers who can assess the situation and identify critical points and propose strategies in situations that require immediate solutions.
Review the inclusion and exclusion criteria. The author informs, “The inclusion criteria were: hospital admissions with a medical diagnosis of COVID-19; and be 18 years or older. Individuals under 18 years of age and those who were not hospitalized due to COVID-19 were excluded”, so if being 18 years of age or older is an inclusion criterion and hospital admissions with a medical diagnosis of COVID-19, the exclusion criteria must be those within this population who were included, not being 18 years old and being hospitalized for COVID-19 was already a characteristic or circumstance that prevented the inclusion of the subject in the study.
In the variables, the inclusion criterion is having a diagnosis of COVID-19 and being hospitalized, the diagnostic variable for COVID-19 is not justified since everyone in the study has this outcome. Inform how the risk classification (green, yellow, red and not informed) was defined in the protocol in the study patients. Is it relevant that the author informs the distinction between obesity and overweight, would it not be possible to present this information in a single variable? It is not clear in the text how the authors defined a sedentary lifestyle. It is suggested that age in the bank be presented as a continuous variable, which allows the application of numerous statistical methods with better power for inference and modeling. As the authors inform that they collected data regarding income, the information in the database would be interesting.
As argued by the authors, “open data streamline the research process, facilitate reuse and enrich datasets, in addition to optimizing the application of public resources, that is, enabling greater use of the same investment”, it would be recommended that the authors inform the geographical location of the two hospitals in southern Brazil, as well as better describing the population from which the sample originated.
I understand that this information described by the author “Researchers interested in the sociodemographic and clinical profile of patients hospitalized for COVID-19 can widely explore the variables described here”, is not a limitation.