Chest computed tomography characteristics of critically ill COVID-19 patients with auto-antibodies against type I interferons

Purpose: patients 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.

Methods: Bicentric 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) 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 (±72h). 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.

Results: 231 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 auto-IFN anti-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).

Conclusion: There 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.

Errataetall:

UpdateIn: J Clin Immunol. 2023 Dec 22;44(1):15. - PMID 38129345

Medienart:

E-Artikel

Erscheinungsjahr:

2023

Erschienen:

2023

Enthalten in:

Zur Gesamtaufnahme - year:2023

Enthalten in:

Research square - (2023) vom: 13. Juni

Sprache:

Englisch

Beteiligte Personen:

Rapnouil, Baptiste Lafont [VerfasserIn]
Zaarour, Youssef [VerfasserIn]
Arrestier, Romain [VerfasserIn]
Bastard, Paul [VerfasserIn]
Peiffer, Bastien [VerfasserIn]
Moncomble, Elsa [VerfasserIn]
Parfait, Mélodie [VerfasserIn]
Bellaïche, Raphaël [VerfasserIn]
Casanova, Jean-Laurent [VerfasserIn]
Mekontso-Dessap, Armand [VerfasserIn]
Mule, Sébastien [VerfasserIn]
de Prost, Nicolas [VerfasserIn]

Links:

Volltext

Themen:

Anti-IFN-I antibodies
COVID-19
Critical care
Preprint
Thoracic imaging
Tomodensitometry

Anmerkungen:

Date Revised 01.01.2024

published: Electronic

UpdateIn: J Clin Immunol. 2023 Dec 22;44(1):15. - PMID 38129345

Citation Status PubMed-not-MEDLINE

doi:

10.21203/rs.3.rs-3029654/v1

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM358995582