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

Detalhes bibliográficos
Ano de defesa: 2022
Autor(a) principal: Maira Viana Rego Souza e Silva
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal de Minas Gerais
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: https://hdl.handle.net/1843/46692
Resumo: 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.
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spelling Análise de características hospitalares relacionadas à mortalidade por COVID-19: resultados de um registro hospitalar multicêntrico nacionalCOVID-19SARS-CoV-2Sistemas de SaúdeAssistência HospitalarUnidade de Terapia IntensivaCOVID-19SARS-CoV-2Sistemas de saúdeAssistência hospitalarUnidade de terapia intensivaBackground: 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.CNPq - Conselho Nacional de Desenvolvimento Científico e TecnológicoFAPEMIG - Fundação de Amparo à Pesquisa do Estado de Minas GeraisUniversidade Federal de Minas Gerais2022-10-27T15:10:24Z2025-09-09T00:23:53Z2022-10-27T15:10:24Z2022-03-03info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttps://hdl.handle.net/1843/46692porMaira Viana Rego Souza e Silvainfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFMGinstname:Universidade Federal de Minas Gerais (UFMG)instacron:UFMG2025-09-09T00:23:53Zoai:repositorio.ufmg.br:1843/46692Repositório InstitucionalPUBhttps://repositorio.ufmg.br/oairepositorio@ufmg.bropendoar:2025-09-09T00:23:53Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)false
dc.title.none.fl_str_mv Análise de características hospitalares relacionadas à mortalidade por COVID-19: resultados de um registro hospitalar multicêntrico nacional
title Análise de características hospitalares relacionadas à mortalidade por COVID-19: resultados de um registro hospitalar multicêntrico nacional
spellingShingle Análise de características hospitalares relacionadas à mortalidade por COVID-19: resultados de um registro hospitalar multicêntrico nacional
Maira Viana Rego Souza e Silva
COVID-19
SARS-CoV-2
Sistemas de Saúde
Assistência Hospitalar
Unidade de Terapia Intensiva
COVID-19
SARS-CoV-2
Sistemas de saúde
Assistência hospitalar
Unidade de terapia intensiva
title_short Análise de características hospitalares relacionadas à mortalidade por COVID-19: resultados de um registro hospitalar multicêntrico nacional
title_full Análise de características hospitalares relacionadas à mortalidade por COVID-19: resultados de um registro hospitalar multicêntrico nacional
title_fullStr Análise de características hospitalares relacionadas à mortalidade por COVID-19: resultados de um registro hospitalar multicêntrico nacional
title_full_unstemmed Análise de características hospitalares relacionadas à mortalidade por COVID-19: resultados de um registro hospitalar multicêntrico nacional
title_sort Análise de características hospitalares relacionadas à mortalidade por COVID-19: resultados de um registro hospitalar multicêntrico nacional
author Maira Viana Rego Souza e Silva
author_facet Maira Viana Rego Souza e Silva
author_role author
dc.contributor.author.fl_str_mv Maira Viana Rego Souza e Silva
dc.subject.por.fl_str_mv COVID-19
SARS-CoV-2
Sistemas de Saúde
Assistência Hospitalar
Unidade de Terapia Intensiva
COVID-19
SARS-CoV-2
Sistemas de saúde
Assistência hospitalar
Unidade de terapia intensiva
topic COVID-19
SARS-CoV-2
Sistemas de Saúde
Assistência Hospitalar
Unidade de Terapia Intensiva
COVID-19
SARS-CoV-2
Sistemas de saúde
Assistência hospitalar
Unidade de terapia intensiva
description 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.
publishDate 2022
dc.date.none.fl_str_mv 2022-10-27T15:10:24Z
2022-10-27T15:10:24Z
2022-03-03
2025-09-09T00:23:53Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://hdl.handle.net/1843/46692
url https://hdl.handle.net/1843/46692
dc.language.iso.fl_str_mv por
language por
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Minas Gerais
publisher.none.fl_str_mv Universidade Federal de Minas Gerais
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFMG
instname:Universidade Federal de Minas Gerais (UFMG)
instacron:UFMG
instname_str Universidade Federal de Minas Gerais (UFMG)
instacron_str UFMG
institution UFMG
reponame_str Repositório Institucional da UFMG
collection Repositório Institucional da UFMG
repository.name.fl_str_mv Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)
repository.mail.fl_str_mv repositorio@ufmg.br
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