Evidence map›Paper›PMID 38129345›Full record

Observational studyJournal of clinical immunology2023

Chest Computed Tomography Characteristics of Critically Ill COVID-19 Patients with Auto-antibodies Against Type I Interferons.

Baptiste Lafont Rapnouil, Youssef Zaarour, Romain Arrestier, Paul Bastard, Bastien Peiffer, Elsa Moncomble, Mélodie Parfait, Raphaël Bellaïche, Jean-Laurent Casanova, Armand Mekontso Dessap and 2 more

Open access · hybridAbstract readObservational Study
In one paragraph

Observational study in Journal of clinical immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 38% 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

3 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors at 3 institutions in 2 countries.

Baptiste Lafont RapnouilService de Médecine Intensive Réanimation, Hôpitaux Universitaires Henri Mondor, Assistance Publique-Hôpitaux de Paris, CEDEX, Créteil, 94010, Paris, France.
Youssef ZaarourDépartement d'imagerie médicale, Hôpitaux Universitaires Henri Mondor, Assistance Publique-Hôpitaux de Paris, CEDEX, Créteil, 94010, Paris, France.
Romain ArrestierService de Médecine Intensive Réanimation, Hôpitaux Universitaires Henri Mondor, Assistance Publique-Hôpitaux de Paris, CEDEX, Créteil, 94010, Paris, France.
Paul BastardLaboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM U1163, Necker Hospital for Sick Children, Paris, France.
Bastien PeifferService de Santé Publique, Hôpitaux Universitaires Henri-Mondor, F-94010, Créteil, France.
Elsa MoncombleService de Médecine Intensive Réanimation, Hôpitaux Universitaires Henri Mondor, Assistance Publique-Hôpitaux de Paris, CEDEX, Créteil, 94010, Paris, France.
Mélodie ParfaitService de Médecine Intensive Réanimation, Hôpitaux Universitaires Henri Mondor, Assistance Publique-Hôpitaux de Paris, CEDEX, Créteil, 94010, Paris, France.
Raphaël BellaïcheService d'Anesthésie-Réanimation Chirurgicale, Assistance Publique-Hôpitaux de Paris, Hôpitaux Universitaires Henri Mondor, 94010, Créteil, France.
Jean-Laurent CasanovaLaboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM U1163, Necker Hospital for Sick Children, Paris, France.
Armand Mekontso DessapService de Médecine Intensive Réanimation, Hôpitaux Universitaires Henri Mondor, Assistance Publique-Hôpitaux de Paris, CEDEX, Créteil, 94010, Paris, France.
Sébastien MuleDépartement d'imagerie médicale, Hôpitaux Universitaires Henri Mondor, Assistance Publique-Hôpitaux de Paris, CEDEX, Créteil, 94010, Paris, France.
Nicolas de ProstService de Médecine Intensive Réanimation, Hôpitaux Universitaires Henri Mondor, Assistance Publique-Hôpitaux de Paris, CEDEX, Créteil, 94010, Paris, France. nicolas.de-prost@aphp.fr.ORCID 0000-0002-4833-4320
Inserm · FRAssistance Publique – Hôpitaux de Paris · FRHôpitaux Universitaires Henri-Mondor · FR

Funding

Developing, Demonstrating, and Disseminating Innovative Programs to Achieve Translational SuccessUL1TR001866 · NCATS · ROCKEFELLER UNIVERSITY · PI COLLER, BARRY, KRUEGER, JAMES G · 2016 to 2025
$40.6M
Monogenic basis of resistance to SARS-CoV2 and predisposition to severe COVID-19R01AI088364 · NIAID · UT SOUTHWESTERN MEDICAL CENTER · PI Jean-Laurent Casanova, Shen-Ying Zhang · 2010 to 2026
$8.7M
Inborn errors of immunity in patients with life-threatening COVID-19R01AI163029 · NIAID · ROCKEFELLER UNIVERSITY · PI CASANOVA, JEAN-LAURENT, ZHANG, QIAN · 2021 to 2025
$3.7M
Howard Hughes Medical InstituteNCATS NIH HHS UL1 TR001866NIAID NIH HHS R01 AI088364NIAID NIH HHS R01 AI163029
6 · The paper itself

Abstract

purposePatients with auto-antibodies neutralizing type I interferons (anti-IFN auto-Abs) are at risk of severe forms of coronavirus disease 19 (COVID-19). The chest computed tomography (CT) scan characteristics of critically ill COVID-19 patients harboring these auto-Abs have never been reported.

methodsBicentric ancillary study of the ANTICOV study (observational prospective cohort of severe COVID-19 patients admitted to the intensive care unit (ICU) for hypoxemic acute respiratory failure between March 2020 and May 2021) on chest CT scan characteristics (severity score, parenchymal, pleural, vascular patterns). Anti-IFN auto-Abs were detected using a luciferase neutralization reporting assay. Imaging data were collected through independent blinded reading of two thoracic radiologists of chest CT studies performed at ICU admission (± 72 h). The primary outcome measure was the evaluation of severity by the total severity score (TSS) and the CT severity score (CTSS) according to the presence or absence of anti-IFN auto-Abs.

resultsTwo hundred thirty-one critically ill COVID-19 patients were included in the study (mean age 59.5 ± 12.7 years; males 74.6%). Day 90 mortality was 29.5% (n = 72/244). There was a trend towards more severe radiological lesions in patients with anti-IFN auto-Abs than in others, not reaching statistical significance (median CTSS 27.5 (21.0-34.8) versus 24.0 (19.0-30.0), p = 0.052; median TSS 14.5 (10.2-17.0) versus 12.0 (9.0-15.0), p = 0.070). The extra-parenchymal evaluation found no difference in the proportion of patients with pleural effusion, mediastinal lymphadenopathy, or thymal abnormalities in the two populations. The prevalence of pulmonary embolism was not significantly different between groups (8.7% versus 5.3%, p = 0.623, n = 175).

conclusionThere was no significant difference in disease severity as evaluated by chest CT in severe COVID-19 patients admitted to the ICU for hypoxemic acute respiratory failure with or without anti-IFN auto-Abs.

Indexed as

COVID-19Interferon Type IRespiratory InsufficiencyAgedCritical IllnessFemaleHumansMaleMiddle AgedProspective StudiesSARS-CoV-2Tomography, X-Ray ComputedInterferon Type IAnti-IFN-I antibodiesCOVID-19Critical careThoracic imagingTomodensitometry

Identifiers

PMID38129345
PMCPMC10739505
OpenAlexW4390079454

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.