摘要
目的:探讨基于血管内超声(IVUS)特征及血清学指标构建急性心肌梗死患者院内预后的预测模型。方法:选择2023年6月—2024年6月上饶市人民医院收治的80例急性心肌梗死患者(急性ST段抬高型心肌梗死38例和急性非ST段抬高型心肌梗死42例)为研究对象,根据是否发生院内主要不良心血管事件(MACE)分为MACE组(n=18)、非MACE组(n=62)。对比两组的IVUS特征、血清学指标及基线资料。将两组对比有差异的指标纳入logistic回归分析,并构建及验证相关列线图预测模型。结果:MACE组与非MACE组的最小管腔横截面积(MLA CSA)、斑块负荷、重构指数、甘油三酯-葡萄糖指数、全身免疫炎症指数、肌酸激酶同工酶、N末端B型利钠肽原、病变血管数量对比,差异有统计学意义(P<0.05)。logistic回归分析显示,MLA CSA、斑块负荷、重构指数、甘油三酯-葡萄糖指数、全身免疫炎症指数、肌酸激酶同工酶、病变血管数量均是急性心肌梗死患者院内预后不良的独立影响因素(P<0.05)。列线图模型ROC AUC为0.835[95%CI(0.770,0.897)](P<0.05)。结论:基于IVUS特征及血清学指标构建的列线图预测模型可有效预测急性心肌梗死患者院内预后不良风险。
Objective:To investigate the construction of predictive model for in-hospital prognosis of patients with acute myocardial infarction based on intravascular ultrasound(IVUS)characteristics and serologic indexes.Method:A total of 80 patients with acute myocardial infarction(38 cases of acute ST-segment elevation myocardial infarction and 42 cases of acute non-ST-segment elevation myocardial infarction)admitted to Shangrao People's Hospital from June 2023 to June 2024 were selected as the research subjects.According to whether major adverse cardiovascular events(MACE)occurred in the hospital,they were divided into the MACE group(n=18)and the non-MACE group(n=62).IVUS characteristics,serologic indexes and baseline data of the two groups were compared.The indexes with differences between the two groups were included in the logistic regression analysis,and the related nomogram prediction model was constructed and validated.Result:There were statistically significant differences in minimum lumen area cross-sectional area(MLA CSA),plaque load,remodeling index,triglyceride-glucose index,systemic immune-inflammation index,creatine kinase isoenzyme,N-terminal pro-brain natriuretic peptide,and the number of diseased blood vessels between the MACE group and the non-MACE group(P<0.05).logistic regression analysis showed that MLA CSA,plaque load,remodeling index,triglyceride-glucose index,systemic immune-inflammation index,creatine kinase isoenzyme,and the number of diseased vessels were independent influencing factors for the in-hospital poor prognosis of patients with acute myocardial infarction(P<0.05).The ROC AUC of the nomogram model was 0.835[95%CI(0.770,0.897)](P<0.05).Conclusion:The nomogram prediction model constructed based on IVUS characteristics and serologic indexes can effectively predict the risk of in-hospital poor prognosis in patients with acute myocardial infarction.
作者
邱云章
牟宗阳
杨凯
QIU Yunzhang;MOU Zongyang;YANG Kai(Department of CardiologyⅠ,Shangrao People's Hospital,Shangrao 334000,China;不详)
出处
《中国医学创新》
2025年第23期165-169,共5页
Medical Innovation of China
基金
上饶市指导性科技计划项目(2023CZDX151)。
关键词
急性心肌梗死
院内预后
血管内超声
血清学指标
预测模型
Acute myocardial infarction
In-hospital prognosis
Intravascular ultrasound
Serologic indexes
Predictive modeling
