| 王瑜,李伟,季春艳,等.多参数列线图预测代谢综合征病人并发冠心病的风险[J].安徽医药,2024,28(12):2492-2496. |
| 多参数列线图预测代谢综合征病人并发冠心病的风险 |
| Multiparameter nomogram for predicting coronary heart disease in patients with metabolic syndrome |
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| DOI：10.3969/j.issn.1009-6469.2024.12.032 |
| 中文关键词: 代谢综合征 X 冠心病 心外膜脂肪组织 高密度脂蛋白胆固醇 C反应蛋白 列线图 |
| 英文关键词: Metabolic syndrome X Coronary heart disease Epicardial adipose tissue High-density lipoprotein cholesterol C-reactive protein Nomogram |
| 基金项目:攀枝花学院医学类校级科学研究专项经费( PYYZ-2022-15) |
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| 中文摘要: |
| 目的探讨代谢综合征病人心外膜脂肪组织(EAT)厚度与冠心病的关系，进一步建立和验证早期预测冠心病的列线图预测模型。方法回顾性纳入 2020年 3月至 2023年 1月攀枝花学院附属医院 310例代谢综合征病人，使用随机数字表法按 7∶ 3分配为训练集(n=217)和验证集(n=93)。根据病人冠状动脉造影检查结果，将训练集分为冠心病组( n=64)及非冠心病组(n= 153)。在常规就诊记录中获取两组病人一般资料、生化检测指标及超声心动图参数。采用单因素分析及 logistic回归分析筛选病人发生冠心病的危险因素，并构建列线图预测模型。通过 C-index来评估该列线图的预测准确性和临床价值。结果单因素分析及 logistic回归分析显示总胆固醇( TC)、 C反应蛋白( CRP)、 CRP/高密度脂蛋白胆固醇( HDL-C)、 TC/HDL-C、EAT厚度与冠心病风险相关( P<0.05)。基于上述危险因素建立列线图预测模型，训练集中模型 C-index为 0.89［95%CI:(0.86，0.92)］，验证集中 C-index为 0.73［95%CI:(0.69，0.77)］。结论该研究开发的列线图预测模型结合了代谢综合征病人血脂指标、炎症指标及超声心动图参数，可用于个体化预测冠心病发生风险，以便早期干预及治疗方案的调整。 |
| 英文摘要: |
| Objective To explore the relationship between epicardial adipose tissue (EAT) thickness and coronary heart disease inpatients with metabolic syndrome, and establish and verify a nomogram prediction model for early prediction of coronary heart disease.Methods From March 2020 to January 2023, a total of 310 patients with metabolic syndrome in Affiliated Hospital of Panzhihua Uni-versity were retrospectively enrolled and randomly assigned as training set (n=217) and testing set (n=93). Patients in the training set were divided into coronary heart disease group (n=64) and non-coronary heart disease group (n=153) according to the presence or ab-sence of CH. The general data, biochemical indexes and echocardiographic parameters of the two groups of patients were obtained frompatient records. The risk factors of coronary heart disease were screened by univariate analysis and logistic regression analysis, and anomogram prediction model was constructed. The predictive accuracy and clinical value of the nomogram were evaluated by C-index. Results Univariate analysis and logistic regression showed that total cholesterol (TC), C-reactive protein (CRP), CRP/High density li-poprotein cholesterol (HDL-C), TC/HDL-C and EAT thickness are associated with coronary heart disease risk. A nomogram predictionmodel was established based on the above risk factors. The C-index of the model in the training set was 0.89 [95%CI: (0.86, 0.92)], and the C-index in the testing set was 0.73 [95%CI: (0.69, 0.77)].Conclusion The nomograms developed in the present study combinesplasma lipid, inflammation and echocardiographic parameters in patients with metabolic syndrome, which can be used to individualizethe risk of coronary heart disease for early prevention and treatment. |
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