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Could Metrnl be a New Biomarker to Predict the Development of Macrophage Activation Syndrome in COVID-19 Patients?
Flora ; 28(1):77-86, 2023.
Article in English | EMBASE | ID: covidwho-2290643
ABSTRACT

Introduction:

Failure to maintain the inflammatory and anti-inflammatory balance during COVID-19 treatment may result in a severe clinical course. In our study, we aimed to determine the relationship between the meteorin-like protein (metrnl), which plays a role in the anti-inflammatory balance, and the clinical course. Material(s) and Method(s) Between October 2021 and December 2021, 160 patients who were hospitalized in our hospital and whose delta variant COVID-19 infection was confirmed and 80 healthy controls, were enrolled in the study. Patients were divided into two groups according to the severity degree of COVID-19 (Group 1 Moderate COVID-19, Group 2 Severe COVID-19 MAS). Result(s) When comparing the metrnl levels of the groups, it was observed that the metrnl level was statistically significantly lower in Group 2 patients (p< 0.001). While no statistically significant difference was observed between the healthy control group and Group 1, it was observed that the metrnl level of Group 2 patients was statistically significantly lower than the healthy control group (p= 0.77, <0.001 respectively). In the ROC curve analysis of Metrnl level performed in Group 1 and 2 patients, the cut-off value was taken as 17.54 ng/mL, its sensitivity was observed as 80% and the specificity was observed as 60% in predicting the development of severe COVID-19 in patients whose levels were below this value. Conclusion(s) The low level of metrnl, which is thought to play a key role in anti-inflammatory balance, contributes to the development of macrophage activation syndrome, which leads to the severe clinical course in COVID-19 patients.Copyright © 2023 Bilimsel Tip Yayinevi. All rights reserved.
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Full text: Available Collection: Databases of international organizations Database: EMBASE Type of study: Prognostic study Language: English Journal: Flora Year: 2023 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: EMBASE Type of study: Prognostic study Language: English Journal: Flora Year: 2023 Document Type: Article