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Journal of Infection in Developing Countries
Article . 2024 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Identification of CXCL9 chemokine as a potential biomarker for assessing clinical severity in COVID-19 patients

Authors: Nargiz Ibadullaeva; Aziza Khikmatullaeva; Ulugbek Mirzaev; Nataliya Kan; Marina Bobkova; Erkin Musabaev;

Identification of CXCL9 chemokine as a potential biomarker for assessing clinical severity in COVID-19 patients

Abstract

Introduction: The severity and clinical outcome of COVID-19 depend on virus-specific factors and the host's inflammatory response. Identifying biomarkers of severe COVID-19 is a crucial condition and predicts disease severity. Methodology: This study enrolled a total of 167 patients with COVID-19. These patients were categorized into three groups based on the severity of the disease: moderate course - 78 individuals, severe course - 52 individuals, and extremely severe course - 37 individuals. We analyzed chemokines (IP-10, CXCL9, CCL17) and cytokine IL28B levels using the enzyme immunoassay (EIA) method. Results: CXCL9 levels were increased in severe and extremely severe cases compared to moderate ones. The CCL17 chemokine demonstrated significant elevation in severe cases. However, there was no significant difference in the level of IP-10, and IL28B in the compared groups. Conclusions: Our findings suggest that CXCL9 and CCL17 chemokines could be used as biomarkers to assess the clinical status of patients with COVID-19 and can relate to disease severity. These biomarkers could aid in identifying patients at high risk for severe disease and help guide clinical decision-making for the effective management of COVID-19.

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Keywords

Male, Adult, SARS-CoV-2, IL28B, COVID-19, IP-10, Middle Aged, RC31-1245, Microbiology, Chemokine CXCL9, Severity of Illness Index, QR1-502, CCL17, CXCL9, Humans, Female, Chemokine CCL17, Internal medicine, Biomarkers, Aged

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Top 10%
Average
Average
gold