D105-21 Predicting Infectious Etiology and Severity in Hospitalized Pediatric Pneumonia Using Blood Cytokine Biomarkers

Abstract Background Lower respiratory infections are a significant cause of morbidity and mortality in children. The goal of this study was to determine whether cytokine levels measured in plasma at the time of admission to the hospital can predict disease etiology or severity. Methods We enrolled 159 patients and assessed 59 cytokines against the type of infection and severity. The most prevalent viral infections were human rhinovirus/enterovirus (hRV/EV; 24.4%), respiratory syncytial virus (RSV; 21.8%), and influenza virus (16.7%). Using the concentrations of plasma cytokines, we performed logistic regression and machine learning to determine if we could accurately predict if a child would require longer-term hospitalization ( 5 days), intensive care, or exhibit hypoxemia (SpO2 90%). Results Several cytokines (CHI3L1, IL-1Rα, IL-6, G-CSF, MCP-1, and MIP-1α) were elevated in severe pneumonia cases, regardless of disease etiology. We found that predictors of duration in RSV cases were distinct from other causes, where a type-2 immune response predominated. Cytokines such as chitinase-3-like-1 (CHI3L1), pentraxin-3, osteopontin, and IL-20 correlated with severity across multiple groups. Plasma levels of IL-6, MMP-2 and LIGHT could be used to separate viral versus community acquired pneumonia (CAP). In influenza cases, we could predict longer-term hospitalization and ICU admission based on two cytokines, CHI3L1 and sTNFR1. RSV severity was closely correlated with levels of MIP-1α, IL-26, G-CSF and IFNβ. Conclusions This study highlights the heterogeneity of immune responses to severe pneumonia and provides new groupings of cytokines which may distinguish between viral and non-viral pneumonia. This abstract is funded by: NIH