基于血清学指标构建预测老年急性冠状动脉综合征患者院内不良心血管事件的列线图模型  

A nomogram model based on serological indicators for predicting in-hospital major adverse cardiovascular events in elderly patients with acute coronary syndrome

作　　者：周翔 刘睿涵 刘昱彤 田璠[1] 张杰[1] 王小毛 曹剑[1] Zhou Xiang;Liu Ruihan;Liu Yutong;Tian Fan;Zhang Jie;Wang Xiaomao;Cao Jian(The 4th Healthcare Department of the Second Medical Center,Chinese PLA General Hospital,National Clinical Research Center for Geriatric Diseases,Beijing 100853,China)

机构地区：[1]解放军总医院第二医学中心保健四科,国家老年疾病临床医学研究中心,北京100853

出　　处：《中华老年医学杂志》2025年第3期289-296,共8页Chinese Journal of Geriatrics

基　　金：军队保健课题(21BJZ26)。

摘　　要：目的基于血清学指标构建列线图模型预测老年急性冠状动脉综合征(acute coronary syndrome,ACS)患者院内不良心血管事件(major adverse cardiovascular events,MACE)的发生风险。方法本研究是一项单中心回顾性横断面研究,分析解放军总医院2022年1月至2024年5月诊断的1818例老年ACS患者的临床资料。按照7∶3的比例随机分为训练集(1272例)和验证集(546例);训练集和验证集组间比较后,根据是否发生终点事件将训练集分为非MACE组和MACE组,先后采用单因素、Lasso回归和多因素logistic回归分析筛选院内MACE的影响因素,并构建列线图模型;采用受试者工作特征(receiver operating characteristic,ROC)曲线、校准曲线及决策曲线进行模型评价。结果1818例ACS患者中年龄67(61.0,73.0)岁,男性占比70.4%;训练集和验证集组间比较几乎所有指标(除血小板计数外)差异均无统计学意义(均P>0.05);训练集非MACE组和MACE组年龄、体质指数、中性粒细胞计数、淋巴细胞计数、单核细胞计数、白细胞计数、血红蛋白、红细胞分布宽度、平均血小板体积、C-反应蛋白(C-reactive protein,CRP)、纤维蛋白原、D-二聚体、白蛋白、直接胆红素、肌钙蛋白T(troponin T,TnT)、空腹血糖(fasting blood glucose,FBG)、估算的肾小球滤过率(estimated glomerular filtration rate,eGFR)、尿酸、脑利钠肽前体(N-terminalpro-brainnatriureticpeptide,NT-proBNP)、糖化血红蛋白(haemoglobin A1c,HbA1c)和高密度脂蛋白胆固醇(high density lipoprotein cholesterol,HDL-C)水平比较,差异有统计学意义(均P<0.05);最终筛选出中性粒细胞计数、血红蛋白、红细胞体积分布宽度、CRP、TnT、FBG和NT-proBNP 7个变量构建列线图模型;该模型在训练集和验证集中表现出高区分度(曲线下面积分别为0.86,95%CI:0.82~0.90;0.85,95%CI:0.81~0.90),两个队列的校准曲线显示预测和实际风险估计值之间密切一致,证明模型校准得到改善,决�ObjectiveTo develop a nomogram model utilizing serological indicators for predicting in-hospital major adverse cardiovascular events(MACE)in elderly patients diagnosed with acute coronary syndrome(ACS).MethodsThis study involved a retrospective analysis of clinical data from 1,818 elderly patients with ACS who were treated at the First Medical Center of the General Hospital of the People's Liberation Army from January 2022 to May 2024.The patients were randomly assigned to a training set(1,272 cases)and a validation set(546 cases)in a 7:3 ratio.Following a comparison of the two groups,the training set was further categorized into non-MACE and MACE groups based on the occurrence of endpoint events.Univariate analysis,Lasso regression,and multivariate logistic regression analyses were sequentially employed to identify factors influencing in-hospital MACE and to construct the nomogram model.The performance of the model was assessed using receiver operating characteristic(ROC)curves,calibration curves,and decision curves.ResultsAmong the 1,818 ACS patients,the mean age was 67 years(interquartile range:61.0 to 73.0),with 70.4%being male.Almost all indicators(except platelet count)exhibited no statistically significant differences between the training and validation sets(all P>0.05).However,statistically significant differences(all P<0.05)were observed in age,body mass index,neutrophil count,lymphocyte count,monocyte count,white blood cell count,hemoglobin,red blood cell distribution width,mean platelet volume,C-reactive protein(CRP),fibrinogen,D-dimer,albumin,direct bilirubin,troponin T(TnT),fasting blood glucose(FBG),estimated glomerular filtration rate(eGFR),uric acid,N-terminal pro-B-type natriuretic peptide(NT-proBNP),glycated hemoglobin(HbA1c),and high-density lipoprotein cholesterol(HDL-C)between the non-MACE and MACE groups in the training set.Ultimately,seven variables—neutrophil count,hemoglobin,red blood cell distribution width,CRP,TnT,FBG,and NT-proBNP—were selected to construct the nomogram model.The m

关 键 词：急性冠脉综合征 老年 血清学指标 不良心血管事件 列线图 

分 类 号：R54[医药卫生—心血管疾病]