Evidence map›Paper›PMID 37153411›Full record

ArticleHeliyon2023

Prognostic utility of the chest computed tomography severity score for the requirement of mechanical ventilation and mortality in hospitalized patients with COVID-19.

Yukiyoshi Kimura, Cesar N Cristancho-Rojas, Yumi Kimura-Sandoval, Ramiro Tapia-Sosa, Lorena Guerrero-Torres, Mariana Licano-Zubiate, Monica Chapa-Ibargüengoitia

Open access · goldAbstract read
In one paragraph

Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 44% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. 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

7 authors at 1 institution in 1 country.

Yukiyoshi KimuraDepartment of Radiology, Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran, Vasco de Quiroga 15, Belisario Domínguez Secc 16, Tlalpan, 14080, Mexico City, Mexico.
Cesar N Cristancho-RojasRadiology Department, CT Scanner Group, Puebla 228, Roma Norte, 06700, Mexico City, Mexico.
Yumi Kimura-SandovalDepartment of Radiology, Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran, Vasco de Quiroga 15, Belisario Domínguez Secc 16, Tlalpan, 14080, Mexico City, Mexico.
Ramiro Tapia-SosaDepartment of Gastroenterology, Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran, Vasco de Quiroga 15, Belisario Domínguez Secc 16, Tlalpan, 14080, Mexico City, Mexico.
Lorena Guerrero-TorresDepartment of Infectious Diseases, Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran, Vasco de Quiroga 15, Belisario Domínguez Secc 16, Tlalpan, 14080, Mexico City, Mexico.
Mariana Licano-ZubiateDepartment of Radiology, Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran, Vasco de Quiroga 15, Belisario Domínguez Secc 16, Tlalpan, 14080, Mexico City, Mexico.
Monica Chapa-IbargüengoitiaDepartment of Radiology, Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran, Vasco de Quiroga 15, Belisario Domínguez Secc 16, Tlalpan, 14080, Mexico City, Mexico.
Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán · MX

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To correlate the chest computed tomography severity score (CT-SS) with the need for mechanical ventilation and mortality in hospitalized patients with COVID-19. Materials and methods: The chest CT images of 224 inpatients with COVID-19, confirmed by reverse transcriptase-polymerase chain reaction (RT-PCR), were retrospectively reviewed from April 1 to 25, 2020, in a tertiary health care center. We calculated the CT-SS (dividing each lung into 20 segments and assigning scores of 0, 1, and 2 due to opacification involving 0%, <50%, and ≥50% of each region for a global range of 0-40 points, including both lungs), and collected clinical data. The receiver operating characteristic curve and Youden Index analysis was performed to calculate the CT-SS threshold and accuracy for classification for risk of mortality or MV requirement. Results: 136 men and 88 women were recruited, with an age range of 23-91 years and a mean of 50.17 years; 79 met the MV criteria, and 53 were nonsurvivors. The optimal threshold was >27.5 points for mortality (area under ROC curve >0.96), with a sensitivity of 93% and specificity of 87%, and >25.5 points for the need for MV (area under ROC curve >0.94), with a sensitivity of 90% and specificity of 89%. The Kaplan-Meier curves show a significant difference in mortality by the CT-SS threshold (Log Rank p < 0.001). Conclusions: In our cohort of hospitalized patients with COVID-19, the CT-SS accurately discriminates the need for MV and mortality risk. In conjunction with clinical status and laboratory data, the CT-SS may be a useful imaging tool that could be included in establishing a prognosis for this population.

Indexed as

ChestCOVID-19Diagnostic imagingMultidetector computed tomography

Identifiers

PMID37153411
PMCPMC10151249
OpenAlexW4367678616

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.