早期主动脉硬化风险筛查模型的构建及验证研究  

Construction and Validation of a Screening Model for Early Atherosclerosis Risk in the Aorta

作　　者：周镇森 黄岩 程思为 张小玉 张晓雨[4] 孙婷 杨先军 谢晖 马祖长[2,3] ZHOU Zhensen;HUANG Yan;CHENG Siwei;ZHANG Xiaoyu;ZHANG Xiaoyu;SUN Ting;YANG Xianjun;XIE Hui;MA Zuchang(Department of Nursing,Bengbu Medical University,Bengbu 233030,China;Hefei Institutes of Physical Science,Chinese Academy of Sciences,Hefei 230031,China;University of Science and Technology of China,Hefei 230026,China;Health Management Center,the First Affiliated Hospital of Anhui Medical University,Hefei 230022,China)

机构地区：[1]蚌埠医科大学护理学院,安徽省蚌埠市233030 [2]中科院合肥物质科学研究院,安徽省合肥市230031 [3]中国科学技术大学,安徽省合肥市230026 [4]安徽医科大学第一附属医院健康管理中心,安徽省合肥市230022

出　　处：《中国全科医学》2024年第33期4147-4154,共8页Chinese General Practice

基　　金：国家重点研发计划(2022YFC2010200);国家自然科学基金面上项目(62133004);安徽省教育厅研究生教育质量工程项目(2022lhpysfjd063)。

摘　　要：背景在心血管风险评估领域,主动脉僵硬度被认为是关键的预测指标,颈股脉搏波传导速度(cfPWV)被认为是无创评估主动脉硬化风险的金标准。由于技术难度等挑战,我国cfPWV检测尚未广泛开展。目的本研究旨在开发并验证一种基于心血管危险因素的早期主动脉硬化风险筛查模型,以期替代cfPWV复杂的测量过程,减少对传统测量方法的依赖。方法选取2023年5—11月在安徽医科大学第一附属医院体检中心招募的878名受试者作为研究对象,按照8∶2的比例进行随机抽样分为建模组(n=703)和验证组(n=175)。收集患者一般资料、实验室检查结果及cfPWV。依据cfPWV检查结果和相关指南,将建模组受试者分为无主动脉硬化风险(n=503)和有主动脉硬化风险(n=200)。采用多因素Logistic回归分析并筛选变量,建立列线图评估模型。绘制模型预测主动脉硬化发生风险的受试者工作特征曲线(ROC曲线),以ROC曲线下面积(AUC)、Hosmer-Lemeshow检验评估模型的区分度和校准度,采用Delong检验比较各模型的AUC,采用决策曲线分析(DCA)评估模型临床实用性,并采用Bootstrap法重复采样1000次对模型进行内部验证。结果建模组有主动脉硬化风险者年龄、BMI、收缩压(SBP)、舒张压(DBP)、平均动脉压(MAP)、尿素、空腹血糖(FBG)、低密度脂蛋白胆固醇(LDL-C)、三酰甘油(TG)、总胆固醇(TC)、丙氨酸氨基转移酶(ALT)、天冬氨酸氨基转移酶(AST)、血红蛋白(Hb)、饮酒、血脂异常、糖尿病比例高于无主动脉硬化风险者,肾小球滤过率(GFR)、血小板计数(PLT)低于无主动脉硬化风险者(P<0.05)。多因素Logistic回归分析结果显示年龄(OR=1.112,95%CI=1.082~1.143)、MAP(OR=1.146,95%CI=1.107~1.188)、Hb(OR=1.026,95%CI=1.004~1.049)和FBG(OR=1.353,95%CI=1.076~1.701)是主动脉硬化的独立影响因素(P<0.05)。纳入多因素Logistic回归分析结果差异有统计学意义的指标(年龄、MAP、Hb、FBBackground In the field of cardiovascular risk assessment,aortic stiffness is considered a key predictive indicator,and carotid-femoral pulse wave velocity(cfPWV)is recognized as the gold standard for non-invasive assessment of atherosclerotic risk in the aorta.Due to challenges such as technical difficulty,cfPWV testing has not been widely implemented in China.Objective This study aimed to develop and validate a screening model for early atherosclerotic risk in the aorta based on cardiovascular risk factors,with the intention of replacing the complex measurement process of cfPWV and reducing reliance on traditional measurement methods.Methods A total of 878 participants recruited from the Health Checkup Center of the First Affiliated Hospital of Anhui Medical University between May and November 2023 were selected as research subjects,randomly divided into a model-building group(n=703)and a validation group(n=175)in an 8∶2 ratio.Patient general information,laboratory test results,and cfPWV were collected.Based on the cfPWV examination results and relevant guidelines,participants in the model-building group were divided into those without atherosclerotic risk in the aorta(n=503)and those with atherosclerotic risk in the aorta(n=200).Multifactorial Logistic regression analysis was used to screen variables and establish a nomogram assessment model.The receiver operating characteristic curve(ROC curve)for predicting the risk of atherosclerosis in the aorta was plotted for the model,and the model's discriminative ability and calibration were assessed using the area under the ROC curve(AUC)and the Hosmer-Lemeshow test,respectively.The Delong test was used to compare the AUCs of different models,and decision curve analysis(DCA)was used to assess the clinical utility of the model.Internal validation of the model was performed using the bootstrap method with 1 000 resampling iterations.Results Participants with atherosclerotic risk in the model-building group were older,had higher BMI,systolic blood pressure(SBP),diasto

关 键 词：动脉硬化 主动脉僵硬度 颈股脉搏波传导速度 预测模型 早期筛查 

分 类 号：R543.5[医药卫生—心血管疾病]