[Development of a predictive scoring model for non-response to intravenous immunoglobulin in Kawasaki disease].

Objectives: To explore the predictive factors for non-response to intravenous immunoglobulin (IVIG) in children with Kawasaki disease (KD) and to establish an IVIG non-response prediction scoring model for the Sichuan region.

Methods: A retrospective study was conducted by collecting clinical data from children with KD admitted to four tertiary hospitals in Sichuan Province between 2019 and 2023. Among them, 940 children responded to IVIG, while 74 children did not respond. Multivariate logistic regression analysis was used to identify the predictive factors for non-response to IVIG and to establish a predictive scoring model. The model's effectiveness was assessed using the receiver operating characteristic curve (ROC) and validated with an independent dataset.

Results: Multivariate logistic regression analysis showed that the platelet-to-lymphocyte ratio (PLR), hemoglobin (Hb), serum creatinine, aspartate aminotransferase (AST), and platelet count (PLT) were closely related to non-response to IVIG in children with KD (P<0.05). Based on these indicators, a predictive scoring model was established: PLR > 199, 0.4 points; Hb ≤ 116 g/L, 4 points; AST > 58 U/L, 0.2 points; serum creatinine > 38 µmol/L, 3.9 points; PLT count ≤ 275 × 10⁹/L, 0.3 points. Using this model, children with KD were scored, and a total score greater than 4.3 was considered high risk of non-response to IVIG. The sensitivity of the model in predicting non-response to IVIG was 77.0%, specificity was 65.7%, and the area under the ROC curve was 0.746 (95%CI: 0.688-0.805).

Conclusions: The predictive scoring model based on PLR, Hb, serum creatinine, AST, and PLT demonstrates good predictive performance for non-response to IVIG in children with KD in the Sichuan region and can serve as a reference for clinical decision-making.