Evidence map›Paper›PMID 39167241›Full record

ArticleAnnals of intensive care2024

Derivation and external validation of predictive models for invasive mechanical ventilation in intensive care unit patients with COVID-19.

Gabriel Maia, Camila Marinelli Martins, Victoria Marques, Samantha Christovam, Isabela Prado, Bruno Moraes, Emanuele Rezoagli, Giuseppe Foti, Vanessa Zambelli, Maurizio Cereda and 6 more

Registry-linked trialAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Annals of intensive care, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05663528 (ANALYSIS OF CLINICAL AND LABORATORY VARIABLES WITH PREDICTION CAPABILITY FOR INDICATION OF INVASIVE MECHANICAL VENTILATION IN PATIENTS WITH COVID-19), which is not on this map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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.

NCT05663528 completednot on this map

Analysis of clinical and laboratory variables with prediction capability for indication of invasive mechanical ventilation in patients with covid-19

TypeobservationalSponsorUniversidade Federal do Rio de JaneiroRan2023 to 2024Enrolled350ConditionsCOVID-19Armsorotracheal intubation
3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
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

16 authors.

Gabriel MaiaLaboratory of Pulmonary Investigation, Institute of Biophysics Carlos Chagas Filho, Centro de Ciências da Saúde, Federal University of Rio de Janeiro, Avenida Carlos Chagas Filho, 273, Bloco G-014, Ilha do Fundão, Rio de Janeiro, 21941-902, RJ, Brazil.
Camila Marinelli MartinsAAC&T Research Consulting LTDA, Curitiba, Brazil.
Victoria MarquesLaboratory of Pulmonary Investigation, Institute of Biophysics Carlos Chagas Filho, Centro de Ciências da Saúde, Federal University of Rio de Janeiro, Avenida Carlos Chagas Filho, 273, Bloco G-014, Ilha do Fundão, Rio de Janeiro, 21941-902, RJ, Brazil.
Samantha ChristovamLaboratory of Pulmonary Investigation, Institute of Biophysics Carlos Chagas Filho, Centro de Ciências da Saúde, Federal University of Rio de Janeiro, Avenida Carlos Chagas Filho, 273, Bloco G-014, Ilha do Fundão, Rio de Janeiro, 21941-902, RJ, Brazil.
Isabela PradoLaboratory of Pulmonary Investigation, Institute of Biophysics Carlos Chagas Filho, Centro de Ciências da Saúde, Federal University of Rio de Janeiro, Avenida Carlos Chagas Filho, 273, Bloco G-014, Ilha do Fundão, Rio de Janeiro, 21941-902, RJ, Brazil.
Bruno MoraesDepartment of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA.
Emanuele RezoagliSchool of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy.
Giuseppe FotiSchool of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy.
Vanessa ZambelliSchool of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy.
Maurizio CeredaDepartment of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA.
Lorenzo BerraRespiratory Care Department, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Patricia Rieken Macedo RoccoLaboratory of Pulmonary Investigation, Institute of Biophysics Carlos Chagas Filho, Centro de Ciências da Saúde, Federal University of Rio de Janeiro, Avenida Carlos Chagas Filho, 273, Bloco G-014, Ilha do Fundão, Rio de Janeiro, 21941-902, RJ, Brazil.
Mônica Rodrigues CruzPedro Ernesto University Hospital, State University of Rio de Janeiro, Rio de Janeiro, Brazil.
Cynthia Dos Santos SamaryLaboratory of Pulmonary Investigation, Institute of Biophysics Carlos Chagas Filho, Centro de Ciências da Saúde, Federal University of Rio de Janeiro, Avenida Carlos Chagas Filho, 273, Bloco G-014, Ilha do Fundão, Rio de Janeiro, 21941-902, RJ, Brazil.
Fernando Silva GuimarãesDepartment of Cardiorespiratory and Musculoskeletal Physiotherapy, Faculty of Physiotherapy, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil.
Pedro Leme SilvaLaboratory of Pulmonary Investigation, Institute of Biophysics Carlos Chagas Filho, Centro de Ciências da Saúde, Federal University of Rio de Janeiro, Avenida Carlos Chagas Filho, 273, Bloco G-014, Ilha do Fundão, Rio de Janeiro, 21941-902, RJ, Brazil. pedroleme@biof.ufrj.br.ORCID http://orcid.org/0000-0001-5838-4949

Funding

Conselho Nacional de Desenvolvimento Científico e Tecnológico Conselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível Superior Coordenação de Aperfeiçoamento de Pessoal de Nível SuperiorFundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeironational institute of science and technology for regenerative medicine national institute of science and technology for regenerative medicine
6 · The paper itself

Abstract

backgroundThis study aimed to develop prognostic models for predicting the need for invasive mechanical ventilation (IMV) in intensive care unit (ICU) patients with COVID-19 and compare their performance with the Respiratory rate-OXygenation (ROX) index.

methodsA retrospective cohort study was conducted using data collected between March 2020 and August 2021 at three hospitals in Rio de Janeiro, Brazil. ICU patients aged 18 years and older with a diagnosis of COVID-19 were screened. The exclusion criteria were patients who received IMV within the first 24 h of ICU admission, pregnancy, clinical decision for minimal end-of-life care and missing primary outcome data. Clinical and laboratory variables were collected. Multiple logistic regression analysis was performed to select predictor variables. Models were based on the lowest Akaike Information Criteria (AIC) and lowest AIC with significant p values. Assessment of predictive performance was done for discrimination and calibration. Areas under the curves (AUC)s were compared using DeLong's algorithm. Models were validated externally using an international database.

resultsOf 656 patients screened, 346 patients were included; 155 required IMV (44.8%), 191 did not (55.2%), and 207 patients were male (59.8%). According to the lowest AIC, arterial hypertension, diabetes mellitus, obesity, Sequential Organ Failure Assessment (SOFA) score, heart rate, respiratory rate, peripheral oxygen saturation (SpO

conclusionsIn the development population of ICU patients with COVID-19, SOFA score, SpO2, and respiratory effort signals predicted the need for IMV better than the ROX index. In the external validation population, although the AUCs did not differ significantly, the accuracy was higher when using SOFA score, SpO2, and respiratory effort signals compared to the ROX index. This suggests that these variables may be more useful in predicting the need for IMV in ICU patients with COVID-19. CLINICALTRIALS: GOV IDENTIFIER: NCT05663528.

Indexed as

COVID-19External validationInvasive mechanical ventilationMultiple logistic regressionSOFA scoreSpO2

Identifiers

PMID39167241
PMCPMC11339005

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Registered trials

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.