Evidence map›Paper›PMID 38699403›Full record

ArticlePulmonary medicine2024

Interest of Chest CT to Assess the Prognosis of SARS-CoV-2 Pneumonia: An In-Hospital-Based Experience in Sub-Saharan Africa.

Serge Emmanuel Obe-A-Ndzem Holenn, Tacite Kpanya Mazoba, Désiré Yaya Mukanga, Tyna Bongosepe Zokere, Djo Lungela, Jean-Robert Makulo, Steve Ahuka, Angèle Tanzia Mbongo, Antoine Aundu Molua

Abstract read
In one paragraph

Article in Pulmonary medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Serge Emmanuel Obe-A-Ndzem HolennDepartment of Radiology and Medical Imaging, Hôpital Médecins de nuit SARL, Kinshasa, Democratic Republic of the Congo.ORCID https://orcid.org/0009-0009-9821-8246
Tacite Kpanya MazobaDepartment of Radiology and Medical Imaging, Cliniques Universitaires de Kinshasa, Kinshasa, Democratic Republic of the Congo.ORCID https://orcid.org/0000-0002-9791-6538
Désiré Yaya MukangaDepartment of Radiology and Medical Imaging, Hôpital Médecins de nuit SARL, Kinshasa, Democratic Republic of the Congo.
Tyna Bongosepe ZokereDepartment of Radiology and Medical Imaging, Hôpital Médecins de nuit SARL, Kinshasa, Democratic Republic of the Congo.
Djo LungelaIntensive Care Unit, Hôpital Médecins de nuit SARL, Kinshasa, Democratic Republic of the Congo.
Jean-Robert MakuloCOVID-19 Treatment Center, Cliniques Universitaires de Kinshasa, Kinshasa, Democratic Republic of the Congo.
Steve AhukaDepartment of Microbiology, Cliniques Universitaires de Kinshasa, Kinshasa, Democratic Republic of the Congo.
Angèle Tanzia MbongoDepartment of Radiology and Medical Imaging, Cliniques Universitaires de Kinshasa, Kinshasa, Democratic Republic of the Congo.
Antoine Aundu MoluaDepartment of Radiology and Medical Imaging, Cliniques Universitaires de Kinshasa, Kinshasa, Democratic Republic of the Congo.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Methods: We included all patients with respiratory symptoms (dyspnea, fever, and cough) and/or respiratory failure admitted to the SOS Médecins de nuit SARL hospital, DR Congo, during the 2nd and 3rd waves of the COVID-19 pandemic. The diagnosis of COVID-19 was established based on RT-PCR anti-SARS-CoV-2 tests (G1 (RT-PCR positive) vs. G2 (RT-PCR negative)), and all patients had a chest CT on the day of admission. We retrieved the digital files of patients, precisely the clinical, biological, and chest CT parameters of the day of admission as well as the vital outcome (survival or death). Chest CT were read by a very high-definition console using Advantage Windows software and exported to the hospital network using the RadiAnt DICOM viewer. To determine the threshold for the percentage of lung lesions associated with all-cause mortality, we used ROC curves. Factors associated with death, including chest CT parameters, were investigated using logistic regression analysis. Results: The study included 200 patients (average age 56.2 ± 15.2 years; 19% diabetics and 4.5% obese), and COVID-19 was confirmed among 56% of them (G1). Chest CT showed that ground glass (72.3 vs. 39.8%), crazy paving (69.6 vs. 17.0%), and consolidation (83.9 vs. 22.7%), with bilateral and peripheral locations (68.8 vs. 30.7%), were more frequent in G1 vs. G2 ( Conclusion: The chest CT demonstrated certain characteristic lesions more frequently in patients in whom the diagnosis of COVID-19 was confirmed. The extent of lesions affecting at least half of the lung parenchyma from the first day of admission to hospital increases the risk of death by a factor of 7.

Indexed as

COVID-19SARS-CoV-2Tomography, X-Ray ComputedAdultAgedDemocratic Republic of the CongoFemaleHumansLungMaleMiddle AgedPrognosisRetrospective Studies

Identifiers

PMID38699403
PMCPMC11065491

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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.