Difference in mortality rates in hospitalized COVID-19 patients identified by cytokine profile clustering using a machine learning approach: An outcome prediction alternative.

Autor:	Castro-Castro AC; Centro de Investigación en Enfermedades Tropicales (CIET), Universidad de Costa Rica, San José, Costa Rica., Figueroa-Protti L; Centro de Investigación en Cirugía y Cáncer (CICICA), Universidad de Costa Rica, San José, Costa Rica., Molina-Mora JA; Centro de Investigación en Enfermedades Tropicales (CIET), Universidad de Costa Rica, San José, Costa Rica., Rojas-Salas MP; Centro de Investigación en Hematología y Trastornos Afines (CIHATA), Universidad de Costa Rica, San José, Costa Rica., Villafuerte-Mena D; Centro de Investigación en Hematología y Trastornos Afines (CIHATA), Universidad de Costa Rica, San José, Costa Rica., Suarez-Sánchez MJ; Centro de Investigación en Hematología y Trastornos Afines (CIHATA), Universidad de Costa Rica, San José, Costa Rica., Sanabría-Castro A; Unidad de Investigación, Hospital San Juan de Dios CCSS, San José, Costa Rica.; Departamento de Farmacología, Facultad de Farmacia, Toxicología y Farmacodependencia, Universidad de Costa Rica, San José, Costa Rica., Boza-Calvo C; Centro de Investigación en Hematología y Trastornos Afines (CIHATA), Universidad de Costa Rica, San José, Costa Rica., Calvo-Flores L; Centro de Investigación en Hematología y Trastornos Afines (CIHATA), Universidad de Costa Rica, San José, Costa Rica., Solano-Vargas M; Centro de Investigación en Hematología y Trastornos Afines (CIHATA), Universidad de Costa Rica, San José, Costa Rica., Madrigal-Sánchez JJ; Centro de Investigación en Hematología y Trastornos Afines (CIHATA), Universidad de Costa Rica, San José, Costa Rica., Sibaja-Campos M; Servicio de Neumología, Hospital San Juan de Dios CCSS, San José, Costa Rica., Silesky-Jiménez JI; Unidad de Cuidados Intensivos, Hospital San Juan de Dios CCSS, San José, Costa Rica., Chaverri-Fernández JM; Departamento de Farmacología, Facultad de Farmacia, Toxicología y Farmacodependencia, Universidad de Costa Rica, San José, Costa Rica., Soto-Rodríguez A; Unidad de Investigación, Hospital San Juan de Dios CCSS, San José, Costa Rica., Echeverri-McCandless A; Unidad de Investigación, Hospital San Juan de Dios CCSS, San José, Costa Rica., Rojas-Chaves S; Unidad de Investigación, Hospital San Juan de Dios CCSS, San José, Costa Rica., Landaverde-Recinos D; Servicio de Oncología Médica, Hospital México CCSS, San José, Costa Rica., Weigert A; Faculty of Medicine, Institute of Biochemistry I, Goethe-University Frankfurt, Frankfurt, Germany.; Frankfurt Cancer Institute, Goethe-University Frankfurt, Frankfurt, Germany.; Cardio-Pulmonary Institute (CPI), Frankfurt, Germany.; German Cancer Consortium (DKTK), Partner Site Frankfurt, Frankfurt, Germany., Mora J; Centro de Investigación en Enfermedades Tropicales (CIET), Universidad de Costa Rica, San José, Costa Rica.; Centro de Investigación en Cirugía y Cáncer (CICICA), Universidad de Costa Rica, San José, Costa Rica.
Jazyk:	angličtina
Zdroj:	Frontiers in medicine [Front Med (Lausanne)] 2022 Sep 20; Vol. 9, pp. 987182. Date of Electronic Publication: 2022 Sep 20 (Print Publication: 2022).
DOI:	10.3389/fmed.2022.987182
Abstrakt:	COVID-19 is a disease caused by the novel Coronavirus SARS-CoV-2 causing an acute respiratory disease that can eventually lead to severe acute respiratory syndrome (SARS). An exacerbated inflammatory response is characteristic of SARS-CoV-2 infection, which leads to a cytokine release syndrome also known as cytokine storm associated with the severity of the disease. Considering the importance of this event in the immunopathology of COVID-19, this study analyses cytokine levels of hospitalized patients to identify cytokine profiles associated with severity and mortality. Using a machine learning approach, 3 clusters of COVID-19 hospitalized patients were created based on their cytokine profile. Significant differences in the mortality rate were found among the clusters, associated to different CXCL10/IL-38 ratio. The balance of a CXCL10 induced inflammation with an appropriate immune regulation mediated by the anti-inflammatory cytokine IL-38 appears to generate the adequate immune context to overrule SARS-CoV-2 infection without creating a harmful inflammatory reaction. This study supports the concept that analyzing a single cytokine is insufficient to determine the outcome of a complex disease such as COVID-19, and different strategies incorporating bioinformatic analyses considering a broader immune profile represent a more robust alternative to predict the outcome of hospitalized patients with SARS-CoV-2 infection. Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. (Copyright © 2022 Castro-Castro, Figueroa-Protti, Molina-Mora, Rojas-Salas, Villafuerte-Mena, Suarez-Sánchez, Sanabría-Castro, Boza-Calvo, Calvo-Flores, Solano-Vargas, Madrigal-Sánchez, Sibaja-Campos, Silesky-Jiménez, Chaverri-Fernández, Soto-Rodríguez, Echeverri-McCandless, Rojas-Chaves, Landaverde-Recinos, Weigert and Mora.)
Databáze:	MEDLINE
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