Early Identification And Warning Model Of Vulnerable Coronary Plaques Established

Background and Objective:In recent years,with the improvement of people’s living standards,the incidence and mortality of coronary atherosclerotic heart disease(coronary heart disease)are increasing year by year.Vulnerable atherosclerotic plaque rupture is the main mechanism of acute coronary syndromes(ACS).Therefore,it is very vital to early detect vulnerable plaques and take effective methods to decrease ACS.intravascular ultrasound(IVUS)as the gold standard,by comparing the patients with stable angina pectoris and unstable angina two groups of clinical risk factors,the measurement of plaque in the coronary CT angiography and blood biomarkers differences of indicators,in order to observe the characteristics of the vulnerable plaques,and suggested the vulnerable plaques early warning model,improve the early detection and intervention of vulnerable plaques,reduce the happening of cardiovascular events.Methods:In this study,54 patients with stable angina pectoris(SA)and 47 patients with non-st-segment elevation acute coronary syndrome(nste-acs)were enrolled,Meanwhile,clinical risk factors of the two groups were collected.Patients with stable angina pectoris underwent dual-energy coronary artery CT angiography and blood circulation markers detection.Patients with NSTE-ACS underwent dual-energy coronary artery CT angiography,blood circulation markers,coronary angiography and IVUS.Multivariate Logistic regression model was used to analyze the independent risk factors of vulnerable plaques and establish a noninvasive evaluation model.Results:Univariate analysis of LDL,homocysteine,number of coronary artery lesions,stenosis score,smoking history,vascular calcification in the two groups was statistically significant(P<0.05).Further binary Logistic regression analysis showed that low-density lipoprotein,homocysteine,coronary artery stenosis and smoking history were still risk factors for unstable angina pectoris after controlling for related variables.Modeling:logit(p)=-12.2+1.277 × LDL+0.271 × homocysteine+1.054 ×coronary stenosis+1.469 X smoking history(i.e.0),P>0.356,namely the high-risk group of unstable angina pectoris.Evaluation of the model:the ROC curve of the joint predictor shows that the area under the curve of the joint predictor is the largest,closest to the upper left corner,and the diagnostic accuracy is the highest.Conclusion:Combined with biological,imaging,coronary heart disease risk factors and other indicators,the prediction model can significantly improve the prediction accuracy of unstable angina pectoris compared with a single test index.Non-invasive model evaluation can improve the early identification and intervention of vulnerable plaques,and reduce the occurrence of cardiovascular events.Meaning:For the first time,imaging and blood circulation markers were included as objective evidences to evaluate and predict vulnerable plaques.Based on the vulnerable plaques,the early warning methodology of high-risk patients was sought.Early warning of vulnerable plaques can significantly reduce the mortality,disability and hospitalization rates of patients with coronary heart disease,improve the quality of life and long-term prognosis of patients,and produce significant economic and social benefits.