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Low baseline IFN-γ response could predict hospitalization in COVID-19 patients

The SARS-CoV-2 infection has spread rapidly around the world causing millions of deaths. Several treatments can reduce mortality and hospitalization. However, their efficacy depends on the choice of the molecule and the precise timing of its administration to ensure viral clearance and avoid a delet...

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Detalles Bibliográficos
Autores principales: Cremoni, Marion, Allouche, Jonathan, Graça, Daisy, Zorzi, Kevin, Fernandez, Céline, Teisseyre, Maxime, Benzaken, Sylvia, Ruetsch-Chelli, Caroline, Esnault, Vincent L. M., Dellamonica, Jean, Carles, Michel, Barrière, Jérôme, Ticchioni, Michel, Brglez, Vesna, Seitz-Polski, Barbara
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9548596/
https://www.ncbi.nlm.nih.gov/pubmed/36225915
http://dx.doi.org/10.3389/fimmu.2022.953502
Descripción
Sumario:The SARS-CoV-2 infection has spread rapidly around the world causing millions of deaths. Several treatments can reduce mortality and hospitalization. However, their efficacy depends on the choice of the molecule and the precise timing of its administration to ensure viral clearance and avoid a deleterious inflammatory response. Here, we investigated IFN-γ, assessed by a functional immunoassay, as a predictive biomarker for the risk of hospitalization at an early stage of infection or within one month prior to infection. Individuals with IFN-γ levels below 15 IU/mL were 6.57-times more likely to be hospitalized than those with higher values (p<0.001). As confirmed by multivariable analysis, low IFN-γ levels, age >65 years, and no vaccination were independently associated with hospitalization. In addition, we found a significant inverse correlation between low IFN-γ response and high level of IL-6 in plasma (Spearman’s rho=-0.38, p=0.003). Early analysis of the IFN-γ response in a contact or recently infected subject with SARS-CoV-2 could predict hospitalization and thus help the clinician to choose the appropriate treatment avoiding severe forms of infection and hospitalization.