ORIGINAL RESEARCH article
Front. Immunol.
Sec. Autoimmune and Autoinflammatory Disorders: Autoinflammatory Disorders
Volume 16 - 2025 | doi: 10.3389/fimmu.2025.1632578
Value of Dynamic Changes in Inflammatory Biomarkers for Predicting Intravenous Immunoglobulin Resistance in Children with Kawasaki Disease
Provisionally accepted
Zhi-yuan Liu1
Yidan Zhang1Qianzi Ge1Weiguo Qian1Qiuqin Xu1Miao Hou1Ying Liu1Guanghui Qian1Jiajia Tan1Panpan Liu1Mingyang Zhang1Jing Li1Sheng Zhao2
Lv Haitao1*
Shuhui Wang1*- 1Children's Hospital of Soochow University, Suzhou, China
- 2Anhui Provincial Children's Hospital, hefei, China
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Purpose: This study assessed the predictive value of dynamic laboratory parameter changes before and after intravenous immunoglobulin (IVIG) treatment for IVIG resistance in children with Kawasaki disease (KD). Methods: Children with KD were stratified based on the occurrence of IVIG resistance. Logistic regression analyses were conducted to identify independent risk factors. The predictive performance of variables and their fractional changes (FC) was evaluated through receiver operating characteristic (ROC) curve analysis. Nonlinear associations between predictors and outcomes were examined via restricted cubic spline (RCS) analysis. Results: The Soochow cohort analyzed 1,796 children, with IVIG resistance observed in 140 cases (7.8%). 636 children from the Anhui cohort were included in external validation. Multivariate regression analysis identified pre-treatment CLR and Hb, post-treatment CLR, LMR, NLR, Hb, and FCs in WBC, Hb, NE%, and NE count as significant independent predictors of IVIG resistance (P < 0.05). ROC analysis demonstrated that WBC(FC) and NE count(FC) were the strongest predictors of IVIG resistance, with AUCs of 0.7677 and 0.7818, respectively, outperforming other parameters. The combined AUC of FC was 0.8307 in the Soochow cohort and 0.8564 in the validation cohort. RCS analysis revealed significant nonlinear relationships between predictors and IVIG resistance. Conclusion: Fractional changes in WBC and NE count were established as robust predictors of IVIG resistance in KD. Future efforts should focus on developing predictive models with thresholds and dynamic risk assessments at various time points to enhance the accuracy of IVIG resistance prediction. Clinicians should closely monitor children with IVIG resistance risk factors and reassess the risk after first treatment.
Keywords: kawasaki disease, fractional changes, Inflammatory biomarkers, Intravenous Immunoglobulin, predictors
Received: 21 May 2025; Accepted: 05 Sep 2025.
Copyright: © 2025 Liu, Zhang, Ge, Qian, Xu, Hou, Liu, Qian, Tan, Liu, Zhang, Li, Zhao, Haitao and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Lv Haitao, Children's Hospital of Soochow University, Suzhou, China
Shuhui Wang, Children's Hospital of Soochow University, Suzhou, China
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