Study on the correlation between Doppler ultrasound features of carotid artery stenosis and the incidence of ischemic stroke

GONG Yuanfang; CHEN Ping; ZHANG Hao; DUAN Pengcang; ZHANG Shuyan; WEN Yongfei; WANG Zhipei

Abstract：Objective To explore the association between the ultrasonic characteristics of carotid artery stenosis(CAS)pa-tients and the incidence of ischemic stroke(CIS)patients assessed by carotid color Doppler ultrasound.Methods Clinical data of 106 CAS patients admitted to our hospital were retrospectively analyzed,and those patients were divided into symptom-atic group(n=46)and asymptomatic group(n=60)according to the incidence of CIS symptoms on the same side and in the same basin in the recent 6 months.Differences in general data and ultrasound characteristics between the two groups were analyzed by one-way variance.The indicators with statistical differences were included in the analysis of binary Logistic regression model to analyze the related influencing factors of CIS symptoms.ROC curve was used to analyze the value of ultrasonic characteristics of CAS patients in predicting the incidence of CIS.Results The rate of carotid artery stenosis(70%-99%),the surface morphol-ogy of plaque(irregular)and the classification of neovascularization in plaque(grade Ⅰ～Ⅱ)in symptomatic group were higher than those in asymptomatic group(P<0.05).Binary Logistic regression analysis showed that carotid artery stenosis rate(70%～99%),plaque surface morphology(irregular),and intra-plaque neovascularization grade(grade Ⅰ～Ⅱ)were risk factors for ischemic stroke in CAS patients(P<0.05).ROC curve analysis showed that the AUC of CIS prediction for carotid artery stenosis patients(carotid artery stenosis rate,plaque surface morphology,and intra-plaque neovasculation)was 0.611,0.740,and 0.836,respectively,with sensitivity of 52.2%,91.3%,and 78.3%.The specificity was 70.0%,56.7%,90.0%,which had cer-tain value in prediction.Conclusion The ultrasonic characteristics of CAS assessed by carotid color Doppler ultrasound can be used as an effective index to predict the incidence of CIS.