Análise de características hospitalares relacionadas à mortalidade por COVID-19: resultados de um registro hospitalar multicêntrico nacional

• Ano de defesa: 2022
• Autor(a) principal: Maira Viana Rego Souza e Silva
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Minas Gerais
• Palavras-chave em Português: COVID-19; SARS-CoV-2; Sistemas de Saúde; Assistência Hospitalar; Unidade de Terapia Intensiva
• Link de acesso: https://hdl.handle.net/1843/46692

Background: The COVID-19 pandemic caused unprecedented pressure over health care systems worldwide. Hospital-level data that may influence the prognosis in COVID-19 patients still needs to be better investigated. Therefore, this study analyzed regional socioeconomic, general hospital, and intensive care units (ICU)-specific characteristics associated with in-hospital mortality in COVID-19 patients admitted to Brazilian institutions. Methods: This multicenter retrospective cohort study is part of the Brazilian COVID-19 Registry. Patients ≥18 years-old with laboratory-confirmed COVID-19 admitted to the participating hospitals from March to September 2020, were enrolled. Patients’ data were obtained through hospital records. Hospitals’ data were collected through forms filled in loco and through open national databases. Generalized linear mixed models with logit link function were used for pooling mortality and to assess association between hospital characteristics and mortality estimates. Two models were built, one testing general and regional hospital characteristics and another testing ICU-specific organizational factors. All analyses were adjusted for the proportion of high-risk patients at admission. Results: Thirty-one hospitals were included. The mean number of beds was 320.4 ± 186.6, 19 hospitals were academic, and 22 were COVID-19 reference centers. Estimated in-hospital mortality ranged from 9.0% to 48.0%. The first model included those 31 hospitals and showed that a private source of funding (β=-0.37; 95%CI: -0.71 to -0.04; p=0.029) and location in areas with a high gross domestic product (GDP) per capita (β=-0.40; 95%CI: -0.72 to -0.08; p=0.014) were independently associated with lower mortality. The second model included 23 hospitals and showed that a hospital with a more experienced medical staff in the ICU work shift with a higher proportion of intensivists (β=-0.59; 95%CI: -0.98 to -0.20; p=0.003) and lower proportion of medical residents (β=-0.40; 95%CI: -0.68 to -0.11; p=0.006) were independently associated with lower mortality. Conclusions: In-hospital mortality varied significantly among Brazilian hospitals. Private-funded hospitals and those located in municipalities with a high GDP had lower mortality. When analyzing ICU-specific characteristics, a more experienced medical staff was associated with lower mortality.