基于Hcy、NT-proBNP及FAR水平构建川崎病冠脉病变预警模型及早期分层药物治疗策略的临床研究

Clinical Study on the Construction of an Early Warning Model and Early Stratified Drug Therapy Strategies for Coronary Artery Lesions in Kawasaki Disease Based on Hcy, NT-proBNP, and FAR Levels

摘要: 目的：探讨血清同型半胱氨酸(Hcy)、N末端脑钠肽前体(NT-proBNP)及纤维蛋白原/白蛋白比值(FAR)对儿童川崎病(KD)冠脉病变(CAL)的预测价值，并构建联合预测模型，为CAL的早期风险评估提供参考。方法：回顾性分析60例KD患儿(CAL组26例，非CAL组34例)临床资料。通过多因素Logistic回归筛选CAL独立危险因素并构建预测模型，利用ROC曲线评价其诊断效能，并基于模型风险评分(RS)拟定分层干预策略。结果：1) CAL组血清Hcy、NT-proBNP及FAR水平均显著高于非CAL组(均P < 0.001)；相关性分析显示，Hcy (r = 0.685)、NT-proBNP (r = 0.668)及FAR (r = 0.693)与冠脉Z值均呈显著正相关(均P < 0.05)。2) 年龄(OR = 0.218, P = 0.002)与Hcy (OR = 2.457, P = 0.020)是KD合并CAL的独立危险因素。3) 构建年龄、血清Hcy、NT-proBNP及FAR的多维度联合预警模型，其AUC达0.909，以RS ≥ 0.515为截断值时灵敏度为88.50%，特异度为91.20%，提示该模型具有较好的风险区分能力。结论：年龄和Hcy是KD患儿发生CAL的独立影响因素。基于年龄、Hcy、NT-proBNP及FAR构建的联合预测模型具有较好的预测效能，可为CAL早期风险评估提供参考。

Abstract: Objective: To investigate the predictive value of serum homocysteine (Hcy), N-terminal pro-brain natriuretic peptide (NT-proBNP), and fibrinogen-to-albumin ratio (FAR) for coronary artery lesions (CAL) in children with Kawasaki disease (KD), and to develop a quantitative stratified pharmacological intervention pathway based on the combined model. Methods: Clinical data from 60 children with KD (26 in the CAL group and 34 in the non-CAL group) were retrospectively analyzed. Multivariate logistic regression analysis was performed to identify independent risk factors for CAL and to construct a predictive model. The performance of the model was evaluated using receiver operating characteristic (ROC) curves. Subsequently, a clinical stratified medication protocol was developed based on the model-derived risk scores. Results: 1) The serum levels of Hcy, NT-proBNP, and FAR in the CAL group were significantly higher than those in the non-CAL group (all P < 0.001). Correlation analysis revealed that Hcy (r = 0.685), NT-proBNP (r = 0.668), and FAR (r = 0.693) were all significantly and positively correlated with coronary Z-scores (all P < 0.05). 2) Multivariate logistic regression analysis identified that age (OR = 0.218, P = 0.002) and Hcy (OR = 2.457, P = 0.02) were independent risk factors for CAL in children with KD. 3) A combined prediction model based on age, serum Hcy, NT-proBNP, and FAR was constructed. The model yielded an AUC of 0.909. At an RS cutoff value of 0.515, the sensitivity and specificity were 88.50% and 91.20%, respectively, suggesting that the model may have good discriminatory performance for the early risk assessment of CAL. Conclusion: Age and Hcy were independent factors associated with the development of CAL in children with KD. The combined prediction model based on age, Hcy, NT-proBNP, and FAR showed good predictive performance and may serve as a preliminary tool for the early risk assessment of CAL.