Serum HMGB1 as a biomarker and predictive model for pediatric septic shock: a cohort study

血清HMGB1作为儿童脓毒性休克的生物标志物和预测模型:一项队列研究

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Abstract

BACKGROUND: Sepsis, defined as life-threatening organ dysfunction due to a dysregulated host response to infection, remains a leading cause of pediatric mortality. High mobility group box 1 (HMGB1), a late inflammatory mediator, has shown prognostic value in adult sepsis, but its utility in pediatric populations remains inadequately investigated. This study aimed to evaluate HMGB1 as a prognostic biomarker for septic shock in children with sepsis and to develop a clinical prediction model. METHODS: In this prospective cohort study, we enrolled 46 pediatric patients (aged 1 month to 18 years) with sepsis and organ dysfunction at a tertiary hospital in China (March 2022 to December 2023). Serum HMGB1 levels were measured within 24 hours of admission. Patients were stratified into shock (n=17) and non-shock (n=29) groups. Receiver operating characteristic (ROC) curve analysis evaluated the diagnostic performance of HMGB1 and other biomarkers. Multivariable logistic regression identified independent predictors, which were integrated into a nomogram prediction model. RESULTS: Septic shock developed in 17 patients (37.0%). The shock group exhibited significantly elevated levels of HMGB1, procalcitonin (PCT), serum amyloid A (SAA), interleukin-6 (IL-6), fibrin degradation products, and urea (all P<0.05). ROC analysis showed that HMGB1 [area under the curve (AUC) 0.755], PCT (AUC 0.843), IL-6 (AUC 0.738), and SAA (AUC 0.704) predicted shock development. Multivariable analysis identified HMGB1 and PCT as independent risk factors. The nomogram combining these biomarkers achieved excellent discrimination (C-index 0.869, AUC 0.874) with sensitivity of 82.4% and specificity of 89.7%. CONCLUSIONS: Serum HMGB1, particularly when combined with PCT in a nomogram model, demonstrates excellent prognostic accuracy for early identification of septic shock risk in pediatric sepsis. This practical bedside tool may facilitate timely risk stratification and guide clinical decision-making, though external validation is needed.

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