【摘要】 目的 探讨皮肤黏膜淋巴结综合征，又称川崎病(KD)患儿菌群分布特点，并分析其并发严重心血管后遗症(SCS)的危险因素，构建风险预测列线图模型。方法 回顾性收集2020年1月至2024年12月本院收治的180例KD患儿临床资料，根据发病6个月内冠状动脉超声检查结果，分为无SCS组(NSCS组，n=148)和SCS组(n=32)。比较两组患儿的临床特征及肠道菌群多样性(Chao1、Shannon指数)和物种组成差异；采用Logistic回归分析SCS的独立危险因素，并基于R软件构建列线图预测模型；通过受试者工作特征(ROC)曲线和校准曲线评估模型的区分度和准确度。结果 在肠道菌群中，SCS组Chao1、Shannon指数低于NSCS组(P<0.05);在口腔菌群中，SCS组Chao1、Shannon指数与NSCS组无差异(P>0.05)。在肠道菌群中，SCS组双歧杆菌属、乳杆菌属丰度降低(P<0.05),而肠球菌属、大肠埃希菌属丰度升高(P<0.05);在口腔菌群中，SCS组链球菌属丰度高于NSCS(P<0.05)。较NSCS组，SCS组IVIG无反应率、CRP、ESR、PLT水平显著更高，而ALB水平显著更低(P<0.05)。Logistic回归分析结果表明，IVIG无反应、CRP、ALB是患儿发生SCS的独立危险因素。Hosmer-Lemeshow检验显示，列线图模型预测患儿并发SCS的概率与实际概率无差异(χ~2=4.726,P=0.431),实际概率和预测概率基本一致。ROC结果显示，风险预测模型预测患儿并发SCS的曲线下面积AUC为0.921,特异性为94.59%,敏感性为84.37%。结论 KD患儿并发SCS存在显著的肠道菌群失调，其特征为促炎菌富集和有益菌缺失。本研究构建的融合微生物与临床指标的风险预测模型能有效个体化预测SCS发生风险，为临床早期强化干预提供关键决策支持。更多还原

【Abstract】 Objective To explore the distribution characteristics of the microbiota in children with cutaneous mucosal lymph node syndrome, also known as Kawasaki disease(KD),and to analyze the risk factors for its concurrent severe cardiovascular sequelae(SCS),and to construct a risk prediction nomogram model. Methods The clinical data of 180 children with KD admitted to our hospital from January 2020 to December 2024 were retrospectively collected. According to the results of coronary artery ultrasound examination within 6 months of onset, they were divided into the non-scs group(NSCS group, n=148) and the SCS group(n=32). Compare the clinical characteristics, intestinal flora diversity(Chao1,Shannon index) and species composition differences between the two groups of children. Logistic regression was used to analyze the independent risk factors of SCS,and a nomogram prediction model was constructed based on R software. The discrimination and accuracy of the model were evaluated through the receiver operating characteristic(ROC) curve and the calibration curve. Results In the intestinal microbiota, the Chao1 and Shannon indices in the SCS group were lower than those in the NSCS group(P<0.05). In the oral microbiota, there was no difference in Chao1 and Shannon indices between the SCS group and the NSCS group(P>0.05). In the intestinal microbiota, the abundance of Bifidobacterium and Lactobacillus in the SCS group decreased(P<0.05),while the abundance of Enterococcus and Escherichia coli increased(P<0.05). In the oral microbiota, the abundance of Streptococcus in the SCS group was higher than that in NSCS(P<0.05). Compared with the NSCS group, the non-response rate of IVIG,CRP,ESR and PLT levels in the SCS group were significantly higher, while the ALB level was significantly lower(P<0.05). The results of Logistic regression analysis indicated that non-response to IVIG,CRP,and ALB were independent risk factors for the occurrence of SCS in children. The Hosmer-Lemeshow test showed that there was no difference between the probability predicted by the nomogram model for concurrent SCS in children and the actual probability(χ~2=4.726,P=0.431),and the actual probability was basically consistent with the predicted probability. The ROC results showed that the area under the curve(AUC) of the risk prediction model for predicting concurrent SCS in children was 0.921,with a specificity of 94.59% and a sensitivity of 84.37%. Conclusion There is a significant intestinal flora imbalance in children with KD complicated with SCS,characterized by the enrichment of pro-inflammatory bacteria and the absence of beneficial bacteria. The risk prediction model integrating microorganisms and clinical indicators constructed in this study can effectively predict the risk of SCS occurrence on an individualized basis, providing key decision support for early clinical intensive intervention.更多还原