Evidence map›Paper›PMID 36360974›Full record

Observational studyInternational journal of environmental research and public health2022

COVID-19 Mortality in Public Hospitals in a Brazilian State: An Analysis of the Three Waves of the Pandemic.

Larissa Soares Dell'Antonio, Franciéle Marabotti Costa Leite, Cristiano Soares da Silva Dell'Antonio, Camila Brandão de Souza, Juliana Rodrigues Tovar Garbin, Ana Paula Brioschi Dos Santos, Nésio Fernandes de Medeiros Junior, Luís Carlos Lopes-Júnior

Abstract readObservational Study
In one paragraph

Observational study in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Observational
  3. Article
  4. Review
  5. Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Larissa Soares Dell'AntonioSecretaria de Estado da Saúde do Espírito Santo, Special Epidemiological Surveillance Nucleus, Instituto Capixaba de Ensino, Pesquisa e Inovação (ICEPi), Vitória 29010-120, ES, Brazil.ORCID 0000-0001-5084-2829
Franciéle Marabotti Costa LeiteGraduate Program in Public Health, Federal University of Espírito Santo (U.F.E.S.), Vitoria 29047-105, ES, Brazil.ORCID 0000-0002-6171-6972
Cristiano Soares da Silva Dell'AntonioSecretaria de Estado da Saúde do Espírito Santo, Special Epidemiological Surveillance Nucleus, Instituto Capixaba de Ensino, Pesquisa e Inovação (ICEPi), Vitória 29010-120, ES, Brazil.ORCID 0000-0001-6568-1300
Camila Brandão de SouzaHospital Universitário Cassiano Antônio de Moraes, Vitória 29041-295, ES, Brazil.
Juliana Rodrigues Tovar GarbinSecretaria de Estado da Saúde do Espírito Santo, Special Epidemiological Surveillance Nucleus, Instituto Capixaba de Ensino, Pesquisa e Inovação (ICEPi), Vitória 29010-120, ES, Brazil.
Ana Paula Brioschi Dos SantosSecretaria de Estado da Saúde do Espírito Santo, Special Epidemiological Surveillance Nucleus, Instituto Capixaba de Ensino, Pesquisa e Inovação (ICEPi), Vitória 29010-120, ES, Brazil.
Nésio Fernandes de Medeiros JuniorSecretaria de Estado da Saúde do Espírito Santo, Special Epidemiological Surveillance Nucleus, Instituto Capixaba de Ensino, Pesquisa e Inovação (ICEPi), Vitória 29010-120, ES, Brazil.
Luís Carlos Lopes-JúniorGraduate Program in Public Health, Federal University of Espírito Santo (U.F.E.S.), Vitoria 29047-105, ES, Brazil.ORCID 0000-0002-2424-6510

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo analyze COVID-19 deaths in public hospitals in a Brazilian state, stratified by the three waves of the pandemic, and to test their association with socio-clinical variables.

methodsObservational analytical study, where 5436 deaths by COVID-19 occurred in hospitals of the public network of Espírito Santo, between 1 April 2020, and 31 August 2021, stratified by the three waves of the pandemic, were analyzed. For the bivariate analyses, the Pearson's chi-square, Fisher's Exact or Friedman's tests were performed depending on the Gaussian or non-Gaussian distribution of the data. For the relationship between time from diagnosis to death in each wave, quantile regression was used, and multinomial regression for multiple analyses.

resultsThe mean time between diagnosis and death was 18.5 days in the first wave, 20.5 days in the second wave, and 21.4 days in the third wave. In the first wave, deaths in public hospitals were associated with the following variables: immunodeficiency, obesity, neoplasia, and origin. In the second wave, deaths were associated with education, O

conclusionThe time interval between diagnosis and death can be impacted by several factors, such as: plasticity of the health system, improved clinical management of patients, and the start of vaccination at the end of January 2021, which covered the age group with the higher incidence of deaths. The deaths occurring in public hospitals were associated with socio-clinical characteristics.

Indexed as

COVID-19PandemicsBrazilHospitals, PublicHumansIncidencecoronavirus infectionsCOVID-19epidemiologic monitoringhealth managementmortalitypublic health surveillancepublic hospitals

Identifiers

PMID36360974
PMCPMC9653571

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.