基于RAAS与Syntax评分构建冠心病合并高血压患者PCI治疗近期预后的Nomogram预测模型  

Construct a Nomogram prediction model for the short-term prognosis of coronary heart disease patients with hypertension after PCI based on RAAS and Syntax score

作　　者：喻茂文 覃左丽 汤洪波 王庆忠 谭辉 YU Maowen;QIN Zuoli;TANG Hongbo;WANG Qingzhong;TAN Hui(Departmen Clinical Laboratory,Jintang Hospital of West China Hospital of Sichuan University,Chengdu,Sichuan 610400,China;Departmen Clinical Laboratory,Tongchang Institute,Chengdu,Sichuan 610000,China)

机构地区：[1]四川大学华西医院金堂医院检验科,四川成都610400 [2]同昌检验所实验室检验科,四川成都610000

出　　处：《国际检验医学杂志》2025年第6期719-727,共9页International Journal of Laboratory Medicine

基　　金：成都市卫生健康委科技计划项目(2021210)。

摘　　要：目的基于肾素-血管紧张素-醛固酮(ALD)系统(RAAS)与冠状动脉病变Syntax评分构建冠心病(CAD)合并高血压患者经皮冠状动脉介入术(PCI)治疗近期预后的Nomogram预测模型,为改善患者预后提供有利依据。方法选取2019年6月至2023年4月四川大学华西医院金堂医院收治的310例CAD合并高血压患者,按照7∶3比例随机将310例患者分为训练集(217例)和验证集(93例)。患者均接受PCI治疗,术后随访3个月,统计主要不良心血管事件(MACE)发生情况并据此将训练集进一步分为预后不良组(68例)、预后良好组(149例)。采用多因素Logistic回归模型分析预后不良的危险因素。在训练集中通过R语言包构建Nomogram预测模型,在验证集中采用校准曲线、受试者工作特征(ROC)曲线验证该模型的预测效能。结果训练集与验证集一般资料比较,差异均无统计学意义(P>0.05)。训练集中发生MACE 68例(31.34%),验证集中发生MACE 28例(30.11%)。预后良好组、预后不良组年龄、左室射血分数、肌酸激酶同工酶(CK-MB)、病变血管支数、肾素活性(PRA)、血管紧张素Ⅱ(ANGⅡ)、ALD、术前Syntax评分、N末端B型脑钠肽前体(NT-proBNP)比较,差异有统计学意义(P<0.05)。Pearson相关分析显示,PRA、ANGⅡ、ALD与术前Syntax评分均呈正相关(r=0.613、0.728、0.695,P<0.05)。Lasso回归筛选出年龄、左室射血分数、病变血管支数、PRA、ANGⅡ、ALD、术前Syntax评分。多因素Logistic回归分析结果显示,年龄、左室射血分数、病变血管支数、PRA、ANGⅡ、ALD、术前Syntax评分均是PCI治疗近期预后不良的独立影响因素(OR=4.448、5.153、4.571、3.875、4.914、4.468、5.224,P<0.05)。ROC曲线结果显示,CAD合并高血压患者PCI治疗近期预后不良的Nomogram预测模型在训练集、验证集中预测的曲线下面积分别为0.884(95%CI 0.837~0.931)、0.885(95%CI 0.818~0.953)。校准曲线显示,该模型在训练集和验证集中预测PCI�Objective To construct a Nomogram prediction model for short-term prognosis of coronary heart disease(CAD)patients with hypertension after percutaneous coronary intervention(PCI)based on renin-angiotensin-aldosterone(ALD)system(RAAS)and Syntax score of coronary artery disease,so as to provide a favorable basis for improving the prognosis of patients.Methods A total of 310 CAD patients with hypertension admitted to Jintang Hospital of West China Hospital of Sichuan University from June 2019 to April 2023 were selected.According to the ratio of 7∶3,310 patients were randomly divided into a training set(217 cases)and a validation set(93 cases).All patients underwent PCI and were followed up for 3 months.The training set was further divided into poor prognosis group(n=68)and good prognosis group(n=148)according to the incidence of major adverse cardiovascular events(MACE).Multivariate Logistic regression model was used to analyze the risk factors of poor prognosis.The Nomogram prediction model was constructed by the R language in the training set,and the calibration curve and receiver operating characteristic(ROC)curve were used to verify the prediction efficiency of the model in the validation set.Results There was no significant difference in the general data between the training set and the validation set(P>0.05).MACE occurred in 68 cases(31.34%)in the training set and 28 cases(30.11%)in the validation set.There were significant differences in age,left ventricular ejection fraction,creatine kinase isoenzyme(CK-MB),number of diseased vessels,renin activity(PRA),angiotensinⅡ(ANGⅡ),ALD,preoperative Syntax score and N-terminal pro-B-type brain natriuretic peptide(NT-proBNP)between the good prognosis group and the poor prognosis group(P<0.05).Pearson correlation analysis showed that PRA,ANGⅡ,ALD were positively correlated with preoperative Syntax score(r=0.613,0.728,0.695,P<0.05).Lasso regression analysis included age,left ventricular ejection fraction,number of diseased vessels,PRA,ANGⅡ,ALD,preoperative Synt

关 键 词：冠心病 高血压 经皮冠状动脉介入术 SYNTAX评分 肾素-血管紧张素-醛固酮系统 Nomogram预测模型 

分 类 号：R446.11[医药卫生—诊断学] R541.4[医药卫生—临床医学]