Pro- and anti-inflammatory cytokines signatures at different severity of dengue infection

Autor: Himani Prajapati, Vivek Kumar, Garima Mittal, Yogesh Saxena
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Journal of Family Medicine and Primary Care, Vol 13, Iss 5, Pp 1975-1982 (2024)
Druh dokumentu: article
ISSN: 2249-4863
2278-7135
24440728
DOI: 10.4103/jfmpc.jfmpc_1576_23
Popis: Context: Dengue disease severity and progression are determined by the host immune response, with both pro- and anti-inflammatory cytokines are key mediators. Aims: To study pro- and anti-inflammatory cytokines across dengue severity and as a biomarker for predicting severe dengue infection. Settings and Design: Hospital-based cross-sectional study was conducted on 125 dengue-positive subjects across the 5-60 years age group of either gender in 2022. Methods and Materials: Haematological parameters and blood samples were drawn to measure cytokines IL6, IL-10 and TNF alpha using the ELISA technique. Statistical Analysis: One-way ANOVA and the Kruskal − Wallis test were used to compare the dependent variables across categories of the dengue spectrum. Receiver operating characteristic curve was drawn to calculate the predictability of the cytokines as a predictor of severe dengue. A P < 0.05 was considered significant. Results: 34.4% of cases had severe dengue infection with 53.2% of severe cases reported in >40 years of age. Only IL-6 levels significantly increased (P < 0.01) across the spectrum of dengue infection across age groups >20 years with a consistent and significant fall in platelet levels (P < 0.01). The accuracy of IL-6 to predict severe dengue was 74.4% and platelet count was 16.2%. Conclusions: Only IL-6 cytokine levels were significantly increased across the spectrum of dengue infection observed in age >20 years and can significantly predict the probability of severe dengue by 74% (sensitivity 81.4%). A significant decrease in platelet values is consistent with the severity but is not a good predictor for severe dengue infection.
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