FIBC、NLR测定联合中医辨证在冠心病预测中的应用

Prediction Value of FIBC and NLR Combined with TCM Syndrome Differentiation for Coronary Heart Disease

目的探索纤维蛋白原(FIBC)、中性粒细胞淋巴细胞比值(NLR)测定联合中医辨证对冠心病的预测价值。方法回顾性分析2020年10月至2021年9月期间主诉为胸闷、胸痛并首次行冠脉造影检查的688例患者。根据冠脉狭窄程度,将直径狭窄≥50%列为冠心病组,将直径狭窄<50%分为非冠心病组,比较两组间FIBC、NLR水平差异;非冠心病组分为冠脉硬化组和正常组,将冠心病组和冠脉硬化组根据Gensini积分四分位数法,分为低分组、中分组、高分组和极高分组,分析FIBC、NLR与Gensini积分的相关性。对冠心病组与非冠心病组间基线资料进行统计学分析,后进行多因素Logistic回归分析,建立Logistic回归模型。采用R语言软件利用ROC曲线评价模型区分度,绘制校准度图,用Bootstrap方法进行模型内部验证。结果FIBC、NLR与Gensini积分呈正相关(r=0.322,r=0.436;P<0.01,P<0.01)。FIBC联合NLR对冠心病的诊断效能良好(AUC=0.746)。FIBC、NLR结合中医辨证模型的区分度良好(AUC=0.766),95%CI(0.731,0.802),灵敏度为69.88%,特异度为73.76%,且模型拟合工作效果良好,具有可重复性。结论FIBC、NLR结合中医辨证预测冠心病效果良好。

Objective:To explore the predictive value of fibrinogen(FIBC),neutrophile granulocyte/lymphocyte(NLR)combined with TCM syndrome differentiation for coronary heart disease(CHD).Methods:A retrospective analysis was performed on 688 patients who complained of chest tightness and chest pain and underwent coronary angiography for the first time between October 2020 and September 2021.According to the degree of coronary artery stenosis,diameter stenosis≥50%was classified as CHD group,diameter stenosis<50%was divided into non-CHD group,and FIBC and NLR levels were compared between the two groups.The non-CHD group was divided into coronary artery sclerosis group and normal group.The CHD group and coronary artery sclerosis group were divided into low group,medium group,high group and very high group according to the Gensini score quartile method.The correlation between FIBC,NLR and Gensini score was analyzed.The baseline data between the CHD group and the non-CHD group were statistically analyzed,followed by multiple Logistic regression analysis to establish a Logistic regression model.R language software was used to evaluate the model differentiation by ROC curve,draw the calibration degree diagram,and Bootstrap method was used to verify the model internally.Results:FIBC,NLR were positively correlated with Gensini score(r=0.322,r=0.436;P<0.01,P<0.01).FIBC combined with NLR had good diagnostic efficacy for CHD(AUC=0.746).FIBC and NLR combined with TCM syndrome differentiation model had good differentiation(AUC=0.766),95%CI(0.731,0.802),sensitivity of69.88%,specificity of 73.76%,and model fitting effect was good,with repeatability.Conclusion:FIBC and NLR combined with TCM syndrome differentiation are effective in predicting CHD.