中国肥厚型心肌病患者血栓栓塞事件风险预测模型的构建研究  

Establishment of a Risk Prediction Model for Thrombotic Events in Chinese Patients with Hypertrophic Cardiomyopathy

作　　者：阮海燕 李丽英 张木馨 郑翼[1] 何森[1] RUAN Haiyan;LI Liying;ZHANG Muxin;ZHENG Yi;HE Sen(Department of Cardiology,West China Hospital of Sichuan University,Chengdu 610041,China;Department of Cardiology,Shuangliu District Hospital of Chinese Medicine,Chengdu 610200,China;Department of Cardiology,the First People's Hospital of Longquanyi District,Chengdu 610100,China)

机构地区：[1]四川大学华西医院心内科,四川省成都市610041 [2]四川省成都市双流区中医医院心内科,610200 [3]四川省成都市龙泉驿区第一人民医院心内科,610100

出　　处：《中国全科医学》2023年第8期917-926,共10页Chinese General Practice

基　　金：四川省科技计划资助项目(2022YFS0186);国家自然科学基金资助项目(81600299)。

摘　　要：背景血栓栓塞(TE)事件是肥厚型心肌病(HCM)的重要并发症。目前针对HCM患者TE事件的风险预测,仅国外学者构建了两个模型:HCM Risk-CVA及French HCM score,然而,现有研究发现HCM Risk-CVA模型对于中国HCM患者的临床价值较为有限。目的本研究拟构建适合中国HCM患者的TE事件风险预测模型。方法本研究系回顾性队列研究,收集2010—2018年在四川大学华西医院就诊的537例HCM患者的病例资料。本研究通过电话随访或电子病历系统查询患者就诊记录,每6~12个月随访1次,直至出现终点事件或死亡或研究拟定的评估日期(2019-12-31),终点事件定义为复合性TE事件。采用单因素和多因素Cox回归分析构建风险预测模型,并使用自助重抽样的方法进行内部验证。结果537例患者中,24例患者有不同程度的数据缺失,最终纳入513例患者。中位随访时间为4.2(1.3,6.2)年,随访过程中42例(8.18%)发生TE事件,年发病率为2.10%[95%CI(1.47%,2.73%)]。根据多因素Cox回归模型构建TE事件风险预测模型,最终纳入年龄、既往TE事件、心房颤动及左心室射血分数(LVEF)(P<0.05)。根据回归系数进行权重后,分别赋值构建SAAE score评分模型,即:S=既往脑卒中(stroke)等TE事件,A=心房颤动(atrial fibrillation),A=年龄(age),E=左心室射血分数(left ventricular ejection fraction)。内部验证提示SAAE score在整体人群中区分TE事件的Harrell’s C-指数为0.773[95%CI(0.688,0.858)],校准斜率为1.006;同时,SAAE score在整体人群中对1、3、5年区分TE事件的Harrell’s C-指数分别为0.790、0.799及0.735,校准能力较好。此外,SAAE score在合并/不合并心房颤动的人群中区分TE事件的Harrell’s C-指数分别为0.669[95%CI(0.548,0.791)]及0.647[95%CI(0.498,0.795)],校准能力也较好;同时,在此两类人群中,该模型对1、3、5年TE事件也具有一定价值的区分及校准能力。对于整体人群、合并/不合并心房颤动人群,根据SAAEBackground Thrombotic events are a major complication of hypertrophic cardiomyopathy(HCM).There are only two available risk prediction models for thrombotic events,HCM Risk-CVA score and French HCM score developed by foreign scholars,yet the former one has been found to have limited predictive value in Chinese HCM patients.Objective To develop a risk prediction model for thrombotic events in Chinese patients with HCM.Methods A retrospective cohort study design was used.Five hundred and thirty-seven HCM patients who admitted to West China Hospital of Sichuan University from 2010 to 2018 were recruited.Post-discharge health status was collected by use of telephone follow-up or checking the treatment status recorded in the electronic medical record system once every 6 to 12 months until a composite thrombotic event(defined as the endpoint event)or death occurred or the determined thrombotic risk assessment day of this study(2019-12-31).Univariate and multvariate Cox regression analyses were applied to build a thrombotic risk prediction model,and its internal validation was tested in a resample using the bootstrapping technique.Results Due to data missing,24 cases were excluded,and the other 513 cases were finally included.During a median follow-up of 4.2 years(IQR:1.3-6.2 years),thrombotic events occurred in 42 cases(8.18%),with an annual morbidity rate of 2.10%[95%CI(1.47%,2.73%)].By multivariate Cox regression analysis,age,prior thrombotic event and left ventricular ejection fraction(LVEF)were identified(P<0.05)and used for constructing the formula of SAAE score(S=prior stroke and other thrombotic events,A=atrial fibrillation,A=age,E=LVEF)for predicting thrombotic events after being weighted based on the regression coefficient.Internal validation suggested that SAAE score could discriminate thrombotic events in the whole population{Harrell’s C-index=0.773[95%CI(0.688,0.858)]},with a calibration slope of 1.006,and could well discriminate 1-year,3-year and 5-year thrombotic events(Harrell’s C-index=0.790,0.799,0

关 键 词：心肌病 肥厚性 血栓栓塞 卒中 心房颤动 年龄 射血分数 评分模型 

分 类 号：R542.2[医药卫生—心血管疾病]