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This descriptive study aims to describe the Brazilian scenario of patients hospitalized due to COVID-19 and to analyze the impact of COVID-19 on the Brazilian public health system. Data will be extracted from the largest secondary database of the Brazilian public health system, DATASUS ("Departamento de Informática do Sistema Único de Saúde"), responsible for collecting, processing, analyzing and disseminating health information and statistics in the country. The analysis, performed only on patients hospitalized during the hospitalization episode, will also evaluate the impact of vaccination against COVID-19 on the immunocompromised population compared to the general population.
This is an observational, retrospective, descriptive study based on a secondary database from the Brazilian public health system. Data were collected from three public databases in a large system (DATASUS). These databases are SRAG ("Síndrome Respiratória Acuta"), SIH ("Sistema de Informação Hospitalar"). All data collected are de-identified, which does not allow the identification of sensitive data of participants. The population of this study would be representative of a significant sample of individuals present in the health records system registered with COVID-19. The data included in this study were acquired between January 2021 and December 2023. This analysis will not include data from specific vaccine brands. The data described refer only to the episode of hospitalization related to COVID-19. The primary objective is to describe the demographic and clinical characteristics of individuals hospitalized for COVID-19 between January 2021 and December 2023, stratified by underlying CI, number of vaccine doses received, age, and period of the predominant variant.
As a secondary objective, it is to describe in-hospital mortality due to COVID-19 among individuals hospitalized for COVID-19 between January 2021 and December 2023, stratified by underlying CI, number of non-CI comorbidities, number of vaccine doses received, age, and period of the predominant variant. And also as an exploratory objective, it is expected to describe the use of hospital healthcare resources (HCRU) and the costs associated with hospitalizations related to COVID-19 between January 2021 and December 2023.
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| Measure | Description | Time Frame |
|---|---|---|
| Hospitalization | Descriptive statistics of individuals with COVID-19-related hospitalization for age (mean, SD), age groups (≥18<64, 65-69, 70-79, 80+); | through study completion, an average of 1 year |
| Incidence of hospital mortality | Evaluate the hospital mortality rate due to covid | through study completion, an average of 1 year |
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Inclusion Criteria:
Exclusion Criteria:
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The population included in this study are hospitalized patients with COVID-19 registered in the SRAG and SIH databases; representative of a significant sample of individuals present in the public health registry system in Brazil.
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Research Site | São Paulo | Brazil |
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| Label | URL |
|---|---|
| CSR Synopsis | View source |
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Qualified researchers can request access to anonymized individual patient-level data from AstraZeneca group of companies sponsored clinical trials via the request portal Vivli.org. All requests will be evaluated as per the AZ disclosure commitment: https://astrazenecagrouptrials.pharmacm.com/ST/Submission/Disclosure.
"Yes", indicates that AZ are accepting requests for IPD, but this does not mean all requests will be approved.
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AstraZeneca will meet or exceed data availability as per the commitments made to the EFPIA/PhRMA Data-Sharing Principles. For details of our timelines, please refer to our disclosure commitment at https://astrazenecagrouptrials.pharmacm.com/ST/Submission/Disclosure.
When a request has been approved AstraZeneca will provide access to the anonymized individual patient-level data via secure research environment Vivli.org. A Signed Data Usage Agreement (non-negotiable contract for data accessors) must be in place before accessing requested information
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