Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Multicenter Study
. 2022 Nov;17(8):2299-2313.
doi: 10.1007/s11739-022-03092-9. Epub 2022 Sep 25.

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

Maira Viana Rego Souza-Silva  1 , Patricia Klarmann Ziegelmann  2 , Vandack Nobre  3 , Virginia Mara Reis Gomes  4 , Ana Paula Beck da Silva Etges  5 , Alexandre Vargas Schwarzbold  6 , Aline Gabrielle Sousa Nunes  7 , Amanda de Oliveira Maurílio  8 , Ana Luiza Bahia Alves Scotton  9 , André Soares de Moura Costa  10 , Andressa Barreto Glaeser  11 , Bárbara Lopes Farace  12 , Bruno Nunes Ribeiro  13 , Carolina Marques Ramos  14 , Christiane Corrêa Rodrigues Cimini  15 , Cíntia Alcantara de Carvalho  16 , Claudete Rempel  17 , Daniel Vitório Silveira  7 , Daniela Dos Reis Carazai  18 , Daniela Ponce  19 , Elayne Crestani Pereira  20 , Emanuele Marianne Souza Kroger  14 , Euler Roberto Fernandes Manenti  21 , Evelin Paola de Almeida Cenci  22 , Fernanda Barbosa Lucas  23 , Fernanda Costa Dos Santos  18 , Fernando Anschau  18 , Fernando Antonio Botoni  14 , Fernando Graça Aranha  20 , Filipe Carrilho de Aguiar  24 , Frederico Bartolazzi  23 , Gabriela Petry Crestani  21 , Giovanna Grunewald Vietta  20 , Guilherme Fagundes Nascimento  7 , Helena Carolina Noal  6 , Helena Duani  3 , Heloisa Reniers Vianna  25 , Henrique Cerqueira Guimarães  12 , Joice Coutinho de Alvarenga  16 , José Miguel Chatkin  26 , Júlia Drumond Parreiras de Morais  25 , Juliana da Silva Nogueira Carvalho  24 , Juliana Machado Rugolo  27 , Karen Brasil Ruschel  21 , Lara de Barros Wanderley Gomes  28 , Leonardo Seixas de Oliveira  15 , Liege Barella Zandoná  17 , Lílian Santos Pinheiro  29 , Liliane Souto Pacheco  6 , Luanna da Silva Monteiro Menezes  3 , Lucas de Deus Sousa  9 , Luis Cesar Souto de Moura  30 , Luisa Elem Almeida Santos  31 , Luiz Antonio Nasi  11 , Máderson Alvares de Souza Cabral  3 , Maiara Anschau Floriani  11 , Maíra Dias Souza  32 , Marcelo Carneiro  33 , Mariana Frizzo de Godoy  26 , Marilia Mastrocolla de Almeida Cardoso  27 , Matheus Carvalho Alves Nogueira  10 , Mauro Oscar Soares de Souza Lima  13 , Meire Pereira de Figueiredo  23 , Milton Henriques Guimarães-Júnior  13 , Natália da Cunha Severino Sampaio  34 , Neimy Ramos de Oliveira  34 , Pedro Guido Soares Andrade  35 , Pedro Ledic Assaf  36 , Petrônio José de Lima Martelli  24 , Raphael Castro Martins  30 , Reginaldo Aparecido Valacio  32 , Roberta Pozza  30 , Rochele Mosmann Menezes  33 , Rodolfo Lucas Silva Mourato  8 , Roger Mendes de Abreu  36 , Rufino de Freitas Silva  8 , Saionara Cristina Francisco  36 , Silvana Mangeon Mereilles Guimarães  35 , Silvia Ferreira Araújo  35 , Talita Fischer Oliveira  32 , Tatiana Kurtz  33 , Tatiani Oliveira Fereguetti  34 , Thainara Conceição de Oliveira  22 , Yara Cristina Neves Marques Barbosa Ribeiro  36 , Yuri Carlotto Ramires  37 , Carísi Anne Polanczyk  5   38 , Milena Soriano Marcolino  3
Affiliations
Multicenter Study

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

Maira Viana Rego Souza-Silva et al. Intern Emerg Med. 2022 Nov.

Abstract

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.

Keywords: COVID-19; Healthcare; Hospital; Intensive care; Mortality.

PubMed Disclaimer

Conflict of interest statement

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Figures

Fig. 1
Fig. 1
Flowchart of hospitals and COVID-19 patients included in the study
Fig. 2
Fig. 2
Forest plot showing the mortality estimated (with 95% CI) for each hospital, their main source of funding and the proportion of high-risk patients
See this image and copyright information in PMC

References

    1. Wiersinga WJ, Rhodes A, Cheng AC, Peacock SJ, Prescott HC. Pathophysiology, transmission, diagnosis, and treatment of coronavirus disease 2019 (COVID-19): a review. JAMA. 2020;324(8):782–793. doi: 10.1001/jama.2020.12839. - DOI - PubMed
    1. Walker PGT, Whittaker C, Watson OJ, Baguelin M, Winskill P, Hamlet A, et al. The impact of COVID-19 and strategies for mitigation and suppression in low- and middle-income countries. Science. 2020;369(6502):413–422. doi: 10.1126/science.abc0035. - DOI - PMC - PubMed
    1. Noronha KVMS, Guedes GR, Turra CM, Andrade MV, Botega L, Nogueira D, et al. The COVID-19 pandemic in Brazil: analysis of supply and demand of hospital and ICU beds and mechanical ventilators under different scenarios. Cad Saude Publica. 2020;36(6):e00115320. doi: 10.1590/0102-311X00115320. - DOI - PubMed
    1. Alves L. Brazilian ICUs short of drugs and beds amid COVID-19 surge. Lancet. 2021;397(10283):1431–1432. doi: 10.1016/S0140-6736(21)00836-9. - DOI - PMC - PubMed
    1. World Health Organization (2021) WHO Coronavirus (COVID-19) Dashboard. Avaliable from: https://covid19.who.int. Accessed: 27 Dec 2021

Publication types