2025 年第 5 期 第 20 卷

主动脉瓣上狭窄患者预后预测模型的建立

Establishment of prognostic prediction model for patients with supravalvular aortic stenosis

作者：郎欣月1吕力知2王城3,4王强2刘之光1

英文作者：Lang Xinyue1 Lyu Lizhi2 Wang Cheng34 Wang Qiang2 Liu Zhiguang1

单位：1首都医科大学附属北京安贞医院药事部临床试验机构，北京100029；2首都医科大学附属北京安贞医院小儿心脏中心，北京100029；3中国医学科学院阜外医院小儿心脏中心，北京100037；4云南省阜外心血管病医院心脏外科，昆明650102

英文单位：1Department of Pharmacy and Clinical Trial Unit Beijing Anzhen Hospital Capital Medical University Beijing 100029 China; 2Center for Pediatric Cardiac Beijing Anzhen Hospital Capital Medical University Beijing 100029 China; 3Center for Pediatric Cardiac Fuwai Hospital Chinese Academy of Medical Sciences Beijing 100037 China; 4Department of Cardiac Surgery Yunnan Fuwai Cardiovascular Hospital Kunming 650102 China

关键词：主动脉瓣上狭窄；预测模型；风险因素

英文关键词：Supravalvularaorticstenosis;Predictionmodel;Riskfactors

• 摘要：

• 目的 本研究拟根据国内2个心脏中心的主动脉瓣上狭窄（SVAS）患者资料建立矫治术后远期再狭窄或再干预风险的预测模型。方法 本研究连续入组2002年5月至2020年1月中国医学科学院阜外医院和云南省阜外心血管病医院2个心脏中心的291例诊断为SVAS并接受矫治手术的患者。主要终点指标是术后随访中的再狭窄或再干预（包括再次手术或介入）。Cox回归用于探究影响主要终点指标的风险因素并构建预测模型。通过受试者工作特征曲线确定预测模型的预测效能。结果 291例SVAS患者中，女98例（占33.7%），手术年龄为4.9（2.3，9.9）岁。随访时间为24.0（6.0，54.0）个月。240例患者（82.5%）完成了超声心动图的随访,其中男157例、女83例。随访期间，无死亡事件发生，33例（13.8%）患者发生了再狭窄，8例（3.3%）患者接受了再次干预（包括再次手术或者介入治疗）。多因素Cox回归分析结果显示，Ⅱ型SVAS、合并肺动脉狭窄、合并主动脉瓣狭窄、窦管结合部Z值和窦管结合部压差是影响远期再狭窄或再干预的独立风险因素（均P＜0.05），并被纳入预测模型。预测模型的曲线下面积为0.846（95%置信区间：0.763～0.928）。结论 本研究发现了预测SVAS手术治疗后发生再狭窄或再干预的关键变量。建立了一个能预测SVAS患者术后发生再狭窄或再干预风险的预测模型，可以作为SVAS患者术后个体化风险评估的实用方法。

• Objective The aim of this study is to establish a model to predict the risk of restenosis or reintervention in patients with supravalvular aortic stenosis (SVAS) after surgical repair based on the data of two Chinese heart centers. Methods This study enrolled 291 patients diagnosed with SVAS and underwent surgical repair from two cardiac centers, Fuwai Hospital, Chinese Academy of Medical Sciences and Yunnan Fuwai Cardiovascular Hospital, from May 2002 to January 2020. The primary end point was restenosis or reintervention (reoperation or intervention) during postoperative follow-up. Cox regression was used to explore the risk factors affecting the primary endpoint and to construct a prediction model. The receiver operating characteristic curve was used to determine the predictive efficacy of the prediction model. Results Among 291 SVAS patients, 98 were female (33.7%), and the mediansurgical age was 4.9(2.3, 9.9) years old. The medianfollow-up time was 24.0(6.0, 54.0) months. Echocardiographic follow-up was completed in 240 patients (82.5%), including 157 males and 83 females. During the follow-up period, no death occurred, restenosis occurred in 33 patients (13.8%), and 8 patients (3.3%) underwent reintervention (including reoperation or interventional therapy). Multivariate Cox regression analysis showed that type Ⅱ SVAS, combined with pulmonary artery stenosis, combined with aortic valve stenosis, sinotubular junction Z score and sinotubular junction pressure gradient were independent risk factors for long-term restenosis or reintervention and were included in the prediction model(all P＜0.05). The area under the curve of the prediction model was 0.846 (95% confidence interval: 0.763-0.928). Conclusions  This study identified key variables that predict the occurrence of restenosis or reintervention after surgical treatment of SVAS. A predictive model is established that can predict the risk of restenosis or reintervention in patients after SVAS surgery, which can be used as a practical method for individualized risk assessment of SVAS patients after surgery.