Predictive Value and Diagnostic Potential of IL-10, IL-17A, IL1-β, IL-6, CXCL, and MCP for Severe COVID-19 and COVID-19 Mortality

Abstract

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) necessitates advanced prognostic tools to anticipate disease progression and optimize patient outcomes. This study evaluates the predictive value and diagnostic potential of interleukins interleukin (IL) IL-10, IL-17A, IL1-β, IL-6, chemokine ligand (CXCL), and Monocyte Chemotactic Protein (MCP) for severe coronavirus disease 2019 (COVID-19) and COVID-19 mortality, aiming to correlate cytokine levels with disease severity. Conducted from January 2023 to January 2024, this prospective cohort study involved patients hospitalized with moderate and severe COVID-19 from Romania. This study analyzed statistically significant predictors of severe COVID-19 outcomes. IL-6 and MCP emerged as significant, with hazard ratios (HRs) of 2.35 (95% confidence interval (CI): 1.54-3.59, p = 0.014) and 2.05 (95% CI: 1.22-3.45, p = 0.007), respectively. Compound scores integrating multiple inflammatory markers also demonstrated predictive value; Compound Score 2 had an HR of 2.23 (95% CI: 1.35-3.68, p = 0.002), surpassing most single markers in association with severe disease. Notably, interleukins IL-10 and IL-1β did not show significant associations with disease severity. This study underscores the importance of IL-6 and MCP as robust predictors of severe COVID-19, substantiating their role in clinical assessments to foresee patient deterioration. The utility of compound scores in enhancing predictive accuracy suggests a composite approach may be more effective in clinical settings.

Keywords: COVID-19; SARS-CoV-2; inflammation; respiratory infections.

Figure 1

ROC curve analysis for severe COVID-19 predictors based on inflammatory scores; CXCL—chemokine Ligand; IL—interleukin; MCP—monocyte chemotactic protein; AUC—area under curve.

Figure 2

Forest plot of severe COVID-19 predictors based on inflammatory scores.