摘要
目的基于胱抑素C(CysC)、纤维蛋白原/白蛋白比值(FAR)构建冠状动脉非阻塞性心肌梗死(MINOCA)并发主要不良心血管事件(MACE)的预测模型。方法选取2021年1月至2023年12月张家港澳洋医院收治的MINOCA患者300例,随访6个月根据是否并发MACE分为MACE组(n=82)和非MACE组(n=218)。收集MINOCA患者临床资料,采用全自动生化分析仪检测CysC、FAR。单因素和多因素非条件Logistic回归分析影响MINOCA并发MACE的影响因素;R语言基于CysC、FAR构建MINOCA并发MACE的预测模型,一致性指数评估模型区分能力,校准曲线评估模型准确性,决策曲线评估模型临床效益,霍斯默-莱梅肖检验模型拟合优度,受试者工作特征(ROC)曲线分析模型预测能效。结果随访6个月,300例MINOCA患者MACE并发率为27.33%(82/300)。单因素分析显示,性别、年龄、左心室射血分数(LVEF)、N末端B型利钠肽前体、低密度脂蛋白胆固醇(LDL-C)、血肌酐、纤维蛋白原(FIB)、白蛋白(ALB)、CysC、FAR与MINOCA并发MACE有关(P<0.05)。多因素非条件Logistic回归显示,女性、年龄大、LDL-C高、CysC高、FAR高为MINOCA并发MACE的独立危险因素,LVEF高为独立保护因素(P<0.05)。根据MINOCA并发MACE的独立影响因素建立回归方程[Logit(P)=-15.282+0.328×性别+0.074×年龄-0.074×LVEF+0.970×LDL-C+0.435×CysC+0.441×FAR],一致性指数为0.903(95%CI:0.898~0.907),校准曲线接近理想曲线,决策曲线高于极端曲线,霍斯默-莱梅肖检验检验P>0.05。ROC曲线显示,基于CysC、FAR构建MINOCA并发MACE预测模型预测MINOCA并发MACE的曲线下面积(AUC)为0.903(95%CI:0.863~0.934),敏感度和特异度分别为0.7561、0.9174。结论基于CysC、FAR构建MINOCA并发MACE的预测模型对MINOCA并发MACE有较高的预测能效。
Objective To construct a prediction model for major adverse cardiovascular events(MACE)myocardial infarction with non-obstructive coronary arteries(MINOCA)based on cystatin C(CysC)and fibrinogen albumin ratio(FAR).Methods 300 patients with MINOCA admitted to our hospital from January 2021 to December 2023 were selected,and were divided into the MACE group(82 patients)and the non-MACE group(218 patients)according to whether they had concurrent MACE at the 6-month follow-up.Clinical data of MINOCA patients were collected,and CysC and FAR were detected by fully automated biochemical analyzer.Single-factor and multifactor unconditional logistic regression were used to analyze the influencing factors affecting the concurrent MACE of MINOCA.A prediction model for MINOCA complicating MACE was constructed through the R language based on CysC,FAR.Consistency indices were used to assess the discriminative ability of the model.Calibration curves were used to assess the accuracy of the model.Decision curves were used to assess the clinical effectiveness of the model,While the Hosmer-Lemeshow test for model goodness of fit,and receiver operating characteristic(ROC)curves to analyze model predictive energy efficiency.Results At 6 months of follow-up,the complication rate of MACE was 27.33%(82/300)in 300 patients with MINOCA.Univariate analysis showed that gender,age,left ventricular ejection fraction(LVEF),N-terminal pro B type natriuretic peptide,low-density lipoprotein cholesterol(LDL-C),blood creatinine,FIB,ALB,CysC,and FAR were associated with the complication of MACE in MINOCA(P<0.05).Multifactorial unconditional Logistic regression showed that female,older age,high LDL-C,high CysC,and high FAR were independent risk factors for MINOCA complicating MACE,and high LVEF was an independent protective factor(P<0.05).A regression equation was established based on the independent influences of MINOCA complicating MACE[Logit(P)=-15.282+0.328×sex+0.074×age-0.074×LVEF+0.970×LDL-C+0.435×CysC+0.441×FAR],the consistency index was 0.903(95%CI:0.898 to 0.907),the calibration curve was close to the ideal curve,the decision curve was higher than the extreme curve,and the Hosmer-Lemeshow test yielded P>0.05.The ROC curve showed that the area under the curve of the MINOCA concurrent MACE prediction model constructed on the basis of CysC and FAR predicted MINOCA concurrent MACE with an area under the curve of 0.903(95%CI:0.863 to 0.934),with a sensitivity and specificity of 0.7561 and 0.9174,respectively.Conclusion The prediction model for constructing MINOCA concurrent MACE based on CysC and FAR has high prediction energy efficiency for MINOCA concurrent MACE.
作者
李迪
蒋达兴
朱捷
LI Di;JIANG Daxing;ZHU Jie(Cardiovascular Department,Zhangjiagang Aoyang Hospital,Zhangjiagang,Jiangsu 215600,China)
出处
《转化医学杂志》
2024年第9期1395-1401,共7页
Translational Medicine Journal
基金
张家港市卫生健康委科研项目(ZJGQNKJ202255)。
关键词
冠状动脉非阻塞性心肌梗死
胱抑素C
纤维蛋白原白蛋白比值
主要不良心血管事件
预测模型
Myocardial infarction with non-obstructive coronary arteries
Cystatin C
Fibrinogen-albumin ratio
Major adverse cardiovascular events
Prediction model
