Hospital characteristics associated with COVID-19 mortality: data from the multicenter cohort Brazilian Registry

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, hospital, and intensive care units (ICU) cha...

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Detalles Bibliográficos
Autores principales: Souza-Silva, Maira Viana Rego, Ziegelmann, Patricia Klarmann, Nobre, Vandack, Gomes, Virginia Mara Reis, Etges, Ana Paula Beck da Silva, Schwarzbold, Alexandre Vargas, Nunes, Aline Gabrielle Sousa, Maurílio, Amanda de Oliveira, Scotton, Ana Luiza Bahia Alves, Costa, André Soares de Moura, Glaeser, Andressa Barreto, Farace, Bárbara Lopes, Ribeiro, Bruno Nunes, Ramos, Carolina Marques, Cimini, Christiane Corrêa Rodrigues, de Carvalho, Cíntia Alcantara, Rempel, Claudete, Silveira, Daniel Vitório, Carazai, Daniela dos Reis, Ponce, Daniela, Pereira, Elayne Crestani, Kroger, Emanuele Marianne Souza, Manenti, Euler Roberto Fernandes, Cenci, Evelin Paola de Almeida, Lucas, Fernanda Barbosa, dos Santos, Fernanda Costa, Anschau, Fernando, Botoni, Fernando Antonio, Aranha, Fernando Graça, de Aguiar, Filipe Carrilho, Bartolazzi, Frederico, Crestani, Gabriela Petry, Vietta, Giovanna Grunewald, Nascimento, Guilherme Fagundes, Noal, Helena Carolina, Duani, Helena, Vianna, Heloisa Reniers, Guimarães, Henrique Cerqueira, de Alvarenga, Joice Coutinho, Chatkin, José Miguel, de Morais, Júlia Drumond Parreiras, Carvalho, Juliana da Silva Nogueira, Rugolo, Juliana Machado, Ruschel, Karen Brasil, Gomes, Lara de Barros Wanderley, de Oliveira, Leonardo Seixas, Zandoná, Liege Barella, Pinheiro, Lílian Santos, Pacheco, Liliane Souto, Menezes, Luanna da Silva Monteiro, Sousa, Lucas de Deus, de Moura, Luis Cesar Souto, Santos, Luisa Elem Almeida, Nasi, Luiz Antonio, Cabral, Máderson Alvares de Souza, Floriani, Maiara Anschau, Souza, Maíra Dias, Carneiro, Marcelo, de Godoy, Mariana Frizzo, Cardoso, Marilia Mastrocolla de Almeida, Nogueira, Matheus Carvalho Alves, Lima, Mauro Oscar Soares de Souza, de Figueiredo, Meire Pereira, Guimarães-Júnior, Milton Henriques, Sampaio, Natália da Cunha Severino, de Oliveira, Neimy Ramos, Andrade, Pedro Guido Soares, Assaf, Pedro Ledic, Martelli, Petrônio José de Lima, Martins, Raphael Castro, Valacio, Reginaldo Aparecido, Pozza, Roberta, Menezes, Rochele Mosmann, Mourato, Rodolfo Lucas Silva, de Abreu, Roger Mendes, Silva, Rufino de Freitas, Francisco, Saionara Cristina, Guimarães, Silvana Mangeon Mereilles, Araújo, Silvia Ferreira, Oliveira, Talita Fischer, Kurtz, Tatiana, Fereguetti, Tatiani Oliveira, de Oliveira, Thainara Conceição, Ribeiro, Yara Cristina Neves Marques Barbosa, Ramires, Yuri Carlotto, Polanczyk, Carísi Anne, Marcolino, Milena Soriano
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2022
Materias:
Im - Original
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9510333/
https://www.ncbi.nlm.nih.gov/pubmed/36153772
http://dx.doi.org/10.1007/s11739-022-03092-9
Descripción
Sumario: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, hospital, and intensive care units (ICU) characteristics associated with in-hospital mortality in COVID-19 patients admitted to Brazilian institutions. This multicenter retrospective cohort study is part of the Brazilian COVID-19 Registry. We enrolled patients ≥ 18 years old with laboratory-confirmed COVID-19 admitted to the participating hospitals from March to September 2020. 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 the association between hospital characteristics and mortality estimates. We built two models, one tested general hospital characteristics while the other tested ICU characteristics. All analyses were adjusted for the proportion of high-risk patients at admission. Thirty-one hospitals were included. The mean number of beds was 320.4 ± 186.6. These hospitals had eligible 6556 COVID-19 admissions during the study period. Estimated in-hospital mortality ranged from 9.0 to 48.0%. The first model included all 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 a lower mortality. The second model included 23 hospitals and showed that hospitals with an ICU work shift composed of more than 50% of intensivists (β = − 0.59; 95% CI − 0.98 to − 0.20; p = 0.003) had lower mortality while hospitals with a higher proportion of less experienced medical professionals had higher mortality (β = 0.40; 95% CI 0.11–0.68; p = 0.006). The impact of those association increased according to the proportion of high-risk patients at admission. In-hospital mortality varied significantly among Brazilian hospitals. Private-funded hospitals and those located in municipalities with a high GDP had a lower mortality. When analyzing ICU-specific characteristics, hospitals with more experienced ICU teams had a reduced mortality. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11739-022-03092-9.

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