Evidence map›Paper›PMID 34271868›Full record

ArticleBMC infectious diseases2021

Fatores associados ao óbito em casos confirmados de COVID-19 no estado do Rio de Janeiro.

Marcella Cini Oliveira, Tatiana de Araujo Eleuterio, Allan Bruno de Andrade Corrêa, Lucas Dalsenter Romano da Silva, Renata Coelho Rodrigues, Bruna Andrade de Oliveira, Marlos Melo Martins, Carlos Eduardo Raymundo, Roberto de Andrade Medronho

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in BMC infectious diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.9field-weighted citation impact, top 22% of its field
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

4 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors at 1 institution in 1 country.

Marcella Cini OliveiraFaculdade de Medicina, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brasil. cini.marcella@gmail.com.ORCID https://orcid.org/0000-0001-5305-6823
Tatiana de Araujo EleuterioInstituto de Estudos em Saúde Pública / Faculdade de Medicina, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brasil.ORCID https://orcid.org/0000-0002-8043-2350
Allan Bruno de Andrade CorrêaInstituto de Física, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brasil.
Lucas Dalsenter Romano da SilvaDepartamento de Medicina Preventiva, Instituto de Estudos em Saúde Pública / Faculdade de Medicina, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brasil.ORCID https://orcid.org/0000-0001-6078-4247
Renata Coelho RodriguesFaculdade de Medicina, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brasil.ORCID https://orcid.org/0000-0001-5014-4991
Bruna Andrade de OliveiraFaculdade de Medicina, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brasil.ORCID https://orcid.org/0000-0003-0640-288X
Marlos Melo MartinsDepartment of Child Neurology, Martagão Gesteira Institute of Childcare and Pediatrics, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil.ORCID https://orcid.org/0000-0002-5511-4764
Carlos Eduardo RaymundoInstituto de Estudos em Saúde Pública / Faculdade de Medicina, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brasil.ORCID https://orcid.org/0000-0002-4150-4403
Roberto de Andrade MedronhoInstituto de Estudos em Saúde Pública / Faculdade de Medicina, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brasil.ORCID https://orcid.org/0000-0003-4073-3930
Universidade Federal do Rio de Janeiro · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCOVID-19 can occur asymptomatically, as influenza-like illness, or as more severe forms, which characterize severe acute respiratory syndrome (SARS). Its mortality rate is higher in individuals over 80 years of age and in people with comorbidities, so these constitute the risk group for severe forms of the disease. We analyzed the factors associated with death in confirmed cases of COVID-19 in the state of Rio de Janeiro. This cross-sectional study evaluated the association between individual demographic, clinical, and epidemiological variables and the outcome (death) using data from the Unified Health System information systems.

methodsWe used the extreme boosting gradient (XGBoost) model to analyze the data, which uses decision trees weighted by the estimation difficulty. To evaluate the relevance of each independent variable, we used the SHapley Additive exPlanations (SHAP) metric. From the probabilities generated by the XGBoost model, we transformed the data to the logarithm of odds to estimate the odds ratio for each independent variable.

resultsThis study showed that older individuals of black race/skin color with heart disease or diabetes who had dyspnea or fever were more likely to die.

conclusionsThe early identification of patients who may progress to a more severe form of the disease can help improve the clinical management of patients with COVID-19 and is thus essential to reduce the lethality of the disease.

Indexed as

AdolescentAdultAgedAged, 80 and overBrazilChildChild, PreschoolCitiesComorbidityCOVID-19Cross-Sectional StudiesFemaleHumansInfantInfant, NewbornMaleCoronavirus deathCoronavirus infectionCOVID-19Machine learningPandemicSARS-CoV-2XGBoost

Identifiers

PMID34271868
PMCPMC8283387
OpenAlexW3180385109

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.