Evidence map›Paper›PMID 36355856›Full record

ArticlePloS one2022

SARS due to COVID-19: Predictors of death and profile of adult patients in the state of Rio de Janeiro, 2020.

Tatiana de Araujo Eleuterio, Marcella Cini Oliveira, Mariana Dos Santos Velasco, Rachel de Almeida Menezes, Regina Bontorim Gomes, Marlos Melo Martins, Carlos Eduardo Raymundo, Roberto de Andrade Medronho

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 43% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
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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 at 2 institutions in 1 country.

Tatiana de Araujo EleuterioInstitute of Studies in Public Health, Federal University of Rio de Janeiro, Rio de Janeiro, State of Rio de Janeiro, Brazil.ORCID 0000-0002-8043-2350
Marcella Cini OliveiraFaculty of Medicine, Federal University of Rio de Janeiro, Rio de Janeiro, State of Rio de Janeiro, Brazil.ORCID 0000-0001-5305-6823
Mariana Dos Santos VelascoFaculty of Nursing, State University of Rio de Janeiro, Rio de Janeiro, State of Rio de Janeiro, Brazil.
Rachel de Almeida MenezesFaculty of Nursing, State University of Rio de Janeiro, Rio de Janeiro, State of Rio de Janeiro, Brazil.
Regina Bontorim GomesFaculty of Nursing, State University of Rio de Janeiro, Rio de Janeiro, State of Rio de Janeiro, Brazil.
Marlos Melo MartinsDepartment of Pediatrics, Institute of Child Care and Pediatrics Martagão Gesteira, Federal University of Rio de Janeiro, Rio de Janeiro, State of Rio de Janeiro, Brazil.
Carlos Eduardo RaymundoInstitute of Studies in Public Health, Federal University of Rio de Janeiro, Rio de Janeiro, State of Rio de Janeiro, Brazil.
Roberto de Andrade MedronhoInstitute of Studies in Public Health, Federal University of Rio de Janeiro, Rio de Janeiro, State of Rio de Janeiro, Brazil.ORCID 0000-0003-4073-3930
Universidade Federal do Rio de Janeiro · BRUniversidade do Estado do Rio de Janeiro · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionWe aimed to describe the profile of adult patients and analyze the predictors of death from severe acute respiratory syndrome (SARS) due to coronavirus disease 2019 (COVID-19) in the state of Rio de Janeiro. Knowledge of the predictors of death by COVID-19 in Rio de Janeiro, a state with one of the highest mortality rates in Brazil, is essential to improve health care for these patients.

methodsData from the Information System for Epidemiological Surveillance of Influenza and the Mortality Information System were used. A binary logistic regression model evaluated the outcome of death, sociodemographic data, and clinical-epidemiological and health care covariates. Univariate, bivariate, and multivariate statistics were performed with the R program, version 4.0.0.

resultsOverall, 51,383 cases of SARS due to COVID-19 among adults were reported in the state between March 5 and December 2, 2020. Mortality was high (40.5%). The adjusted final model presented the following predictors of death in SARS patients due to COVID-19: male sex (odds ratio [OR] = 1.10, 95% confidence interval [CI], 1.04-1.17); age (OR = 5.35, 95%CI, 4.88-5.88; ≥75 years); oxygen saturation <95% (OR = 1.48, 95%CI, 1.37-1.59), respiratory distress (OR = 1.31, 95%CI, 1.21-1.41) and dyspnoea (OR = 1.25, 95%CI, 1.15-1.36), the presence of at least one risk factor/comorbidity (OR = 1.32, 95%CI, 1.23-1.42), chronic kidney disease (OR = 1.94, 95%CI, 1.69-2.23), immunosuppression (OR = 1.51, 95%CI, 1.26-1.81) or chronic neurological disease (OR = 1.36, 95%CI, 1.18-1.58), and ventilatory support, invasive (OR = 8.89, 95%CI, 8.08-9.79) or non-invasive (OR = 1.25, 95%CI, 1.15-1.35).

conclusionsFactors associated with death were male sex, old age, oxygen saturation <95%, respiratory distress, dyspnoea, chronic kidney and neurological diseases, immunosuppression, and use of invasive or noninvasive ventilatory support. Identifying factors associated with disease progression can help the clinical management of patients with COVID-19 and improve outcomes.

Indexed as

COVID-19Respiratory Distress SyndromeAdultBrazilDyspneaFemaleHumansMaleRisk Factors

Identifiers

PMID36355856
PMCPMC9648756
OpenAlexW4308701398

What OpenQuestion holds

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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.