Department of Pediatrics, Institute of Pediatric Research, Children's Hospital of Soochow University, P.R. China.
Department of Pediatrics, Fujian Provincial Hospital, Fujian Provincial Clinical College of Fujian Medical University, Fuzhou, P.R. China.
Ann Med. 2022 Dec;54(1):442-453. doi: 10.1080/07853890.2022.2031273.
We aimed to develop a nomogram to predict risk of resistance to intravenous immunoglobulin (IVIG) in children with Kawasaki disease in eastern China.
We retrospectively analysed the data of children with Kawasaki disease who received IVIG during hospitalisation at Soochow University Affiliated Children's Hospital. IVIG resistance was defined as recrudescent or persistent fever ≥36 h after the end of the IVIG infusion. Baseline variables were analysed using least absolute shrinkage and selection operator (LASSO) to identify the predictors of IVIG resistance, which were then used to construct a predictive nomogram. Calibration curve and area under the receiver operating characteristic curve (AUC) were used to evaluate the performance of the model. The predictive nomogram was validated on test sets of external data and prospective data.
Between January 2015 and December 2020, 1293 Kawasaki disease patients were hospitalized in Soochow University Affiliated Children's Hospital. Among them, 72 (5.57%) showed IVIG resistance. LASSO identified haemoglobin, percentage of neutrophils, C-reactive protein level, platelet count, serum albumin, serum sodium, serum alkaline phosphatase, coronary artery damage, and complete Kawasaki disease as risk factors for IVIG resistance. The nomogram constructed using these factors showed satisfactory discriminatory power (AUC, 0.75), and sensitivity (0.74) and specificity (0.64). In the external data and prospective data, the AUC was 0.66 and 0.83, respectively, the sensitivity was 0.86 and 1, respectively, and the specificity was 0.49 and 0.60, respectively.
The predictive nomogram constructed using nine factors associated with IVIG resistance in children with Kawasaki disease could be a useful tool for identifying patients likely to show IVIG resistance. This nomogram may help reduce the risk of coronary artery lesions.Key MessagesNone of the IVIG resistance scoring systems has shown consistently good performance in previous studies. Tools to predict the risk of IVIG resistance in eastern China are lacking.In our series, haemoglobin level, percentage of neutrophils, platelet count, coronary artery damage, incomplete Kawasaki disease, and CRP, serum albumin, serum sodium, and serum alkaline phosphatase levels were risk factors of IVIG resistance in hospitalized children in the eastern China cities of Suzhou and Fuzhou.We propose an easy-to-use nomogram to predict the risk factors of IVIG resistance in hospitalized children.
本研究旨在构建预测中国东部地区川崎病患儿静脉注射免疫球蛋白（IVIG）耐药风险的列线图。
本研究回顾性分析了苏州大学附属儿童医院住院川崎病患儿的临床资料。IVIG 耐药定义为 IVIG 输注结束后≥36 h 出现复发性或持续性发热。采用最小绝对收缩和选择算子（LASSO）分析基线变量，筛选出 IVIG 耐药的预测因子，并构建预测列线图。采用校准曲线和受试者工作特征曲线下面积（AUC）评估模型效能。采用外部数据和前瞻性数据对预测列线图进行验证。
2015 年 1 月至 2020 年 12 月，苏州大学附属儿童医院共收治 1293 例川崎病患儿，其中 72 例（5.57%）出现 IVIG 耐药。LASSO 分析发现，血红蛋白、中性粒细胞百分比、C 反应蛋白水平、血小板计数、血清白蛋白、血清钠、血清碱性磷酸酶、冠状动脉损伤和不完全川崎病是 IVIG 耐药的危险因素。采用这些因素构建的列线图具有较好的判别能力（AUC=0.75），且灵敏度为 0.74，特异度为 0.64。在外部数据和前瞻性数据中，AUC 分别为 0.66 和 0.83，灵敏度分别为 0.86 和 1，特异度分别为 0.49 和 0.60。
采用与中国东部地区川崎病患儿 IVIG 耐药相关的 9 个因素构建的预测列线图，可用于识别可能出现 IVIG 耐药的患儿，有助于降低冠状动脉损伤风险。关键词：无；IVIG 耐药评分系统在既往研究中的表现均不一致；预测中国东部地区 IVIG 耐药风险的工具缺乏；在本研究系列中，血红蛋白水平、中性粒细胞百分比、血小板计数、冠状动脉损伤、不完全川崎病和 C 反应蛋白、血清白蛋白、血清钠和血清碱性磷酸酶水平是苏州和福州东部地区住院患儿 IVIG 耐药的危险因素；我们提出了一种简单易用的列线图，用于预测住院患儿 IVIG 耐药的风险因素。
