目的 探讨川崎病（Kawasaki disease, KD）儿童静脉注射免疫球蛋白（intravenous immunoglobulin, IVIG）无反应的预测因素，并建立服务于四川地区的IVIG无反应预测评分模型。 方法 回顾性收集2019—2023年四川省4家三级甲等医院收治的KD患儿临床资料，其中IVIG有反应患儿940例，IVIG无反应患儿74例。采用多因素logistic回归分析筛选IVIG无反应发生的预测指标并建立预测评分模型，采用受试者操作特征曲线（receiver operating characteristic curve, ROC曲线）衡量模型效能并利用独立数据集验证该模型。 结果 多因素logistic回归分析显示，血小板与淋巴细胞比值（platelet-to-lymphocyte ratio, PLR）、Hb、血肌酐、谷草转氨酶（aspartate aminotransferase, AST）、PLT计数与KD患儿发生IVIG无反应密切相关（P<0.05），以上述指标建立预测评分模型：PLR>199，赋值0.4分；Hb≤116 g/L，赋值4分；AST>58 U/L，赋值0.2分；血肌酐>38 μmol/L，赋值3.9分；PLT计数≤275×109/L，赋值0.3分。应用该预测评分模型对KD患儿进行评分，确定总分>4.3分提示IVIG无反应高危。该模型预测IVIG无反应的灵敏度为77.0%，特异度为65.7%，受试者操作特征曲线下面积为0.746（95%CI：0.688~0.805）。 结论 以PLR、Hb、血肌酐、AST、PLT计数为评分项目构建的预测评分模型对四川地区IVIG无反应型KD具有一定的预测性能，可为临床决策提供参考。
Abstract
Objective 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.
关键词
川崎病 /
静脉注射免疫球蛋白无反应 /
预测评分模型 /
儿童
Key words
Kawasaki disease /
Non-response to intravenous immunoglobulin /
Predictive scoring model /
Child
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基金
成都市科技项目（2022-YF05-01297-SN）。
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