| Objective: To analyze the application value of vascular endothelial function test in the detection of endothelial cells in the clinical diagnosis of coronary heart disease,and to provide a reference basis for the clinical diagnosis,disease prediction and evaluation of coronary heart disease,so as to guide the clinical rational formulation of prevention and treatment programs.Methods: This study included 200 patients with coronary heart disease who were treated and treated in the Department of Cardiac Rehabilitation,Affiliated Hospital of Changchun University of Traditional Chinese Medicine from January2017 to December 2019,including 116 males and 84 females;age 35 ～82 years old,with an average age of(58.91±6.74)years;95 cases were 1 vessel disease,50 cases were 2 vessel disease,and 55 cases were ≥3 vessel disease.According to coronary artery disease,the number of blood vessels was divided into 1 disease group,2disease groups,and ≥3 disease groups.All patients were examined by UNEXEF38 G ultrasound on admission and calculated endothelium-dependent vasodilation function(FMD),coronary angiography was used to diagnose and statistically score coronary stenosis(CSS),and hospital information management system(HIS)was used as a tool.Collect and record the clinical data of all subjects,including gender,age,smoking,hypertension,diabetes,blood lipid index(LDL,HDL,TG,TC),number of lesions,CSS score,FMD value.Observe and compare the FMD value and CSS score of each subgroup of coronary heart disease;analyze the correlation between FMD and CSS with Pearson’s description,and draw a scatter plot;screen the predictors of the severity of coronary heart disease with general data comparison and multiple linear regression analysis,and then use The R software constructs the Nomogram model,performs ROC curve analysis,and comprehensively evaluates the application value of FMD in the assessment of coronary heart disease.Results:(1)The difference in FMD value of each subgroup of coronary heart disease was statistically significant(F=109.371,P<0.05);and the difference in FMD value of any two groups was statistically significant(P<0.05).(2)The difference in CSS scores of each subgroup of coronary heart disease was statistically significant(F=428.677,P<0.05);and the difference in CSS scores of any two groups was statistically significant(P<0.05).(3)Pearson’s bivariate analysis showed that FMD was negatively correlated with CSS score(r=0.712,P<0.001).(4)The differences in the proportion of smoking,the proportion of combined diabetes,LDL level,and HDL level in patients with coronary heart disease were statistically significant(F(χ2)=4.785,14.533,5.823,4.352,P<0.05)The differences were statistically significant(P<0.05);multiple linear regression analysis confirmed that smoking,diabetes,FMD value,and LDL were independent factors affecting the severity of coronary heart disease(P<0.05);ROC curve analysis showed that smoking,diabetes,LDL,The AUC predicted by FMD to predict the degree of coronary stenosis is 0.398,0.45,0.617,0.908 respectively.The AUC predicted by FMD to predict the degree of coronary stenosis is greater than that of smoking,diabetes,and LDL,and it has more predictive value.Conclusions:(1)The FMD of patients with coronary heart disease decreases,and it becomes more and more obvious with the increase of the number of diseased vessels;(2)The CSS score of patients with coronary heart disease increases with the number of lesions;CSS scores showed a linear negative correlation;(4)smoking,diabetes,FMD value,and LDL were independent factors affecting the degree of coronary artery disease,among which smoking and diabetes were of low value in predicting the degree of disease;LDL predicted the disease The degree has certain accuracy,but it is not ideal;FMD value is highly accurate in predicting the degree of lesions,and it is superior to other predictors,which has clinical application value. |
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