ABSTRACT
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.
ABSTRACT
El Hematoma Subdural crónico es una patología relativamente frecuente que predomina en adultos mayores. Es de inicio insidioso, su diagnóstico se basa en el cuadro clínico y estudios radiológicos como la tomografía computarizada (TAC), el manejo es predominante quirúrgico y su pronóstico es bueno. Se analiza en el presente estudio, una muestra de 95 expedientes clínicos de pacientes con dicho diagnóstico, síntomas iniciales, TAC pre y post diagnóstico, tratamiento y evolución...
