Wall shear stress can improve prediction accuracy for transient ischemic attack

摘要

cqvip:BACKGROUND Early prediction of transient ischemic attack (TIA) has important clinical value. To date, systematic studies on clinical, biochemical, and imaging indicators related to carotid atherosclerosis have been carried out to predict the occurrence of TIA. However, their prediction accuracy is limited. AIM To explore the role of combining wall shear stress (WSS) with conventional predictive indicators in improving the accuracy of TIA prediction. METHODS A total of 250 patients with atherosclerosis who underwent carotid ultrasonography at Naval Military Medical University Affiliated Gongli Hospital were recruited. Plaque location, plaque properties, stenosis rate, peak systolic velocity, and end diastolic velocity were measured and recorded. The WSS distribution map of the proximal and distal ends of the plaque shoulder was drawn using the shear stress quantitative analysis software, and the average values of WSS were recorded. The laboratory indicators of the subjects were recorded. The patients were followed for 4 years. Patients with TIA were included in a TIA group and the remaining patients were included in a control group. The clinical data, laboratory indicators, and ultrasound characteristics of the two groups were analyzed. Survival curves were plotted by the Kaplan-Meier method. Receiver operating characteristic curves were established to evaluate the accuracy of potential indicators in predicting TIA. Logistic regression model was used to establish combined prediction, and the accuracy of combined predictive indicators for TIA was explored.RESULTS The intraclass correlation coefficients of the WSS between the proximal and distal ends of the plaque shoulder were 0.976 and 0.993, respectively, which indicated an excellent agreement. At the end of the follow-up, 30 patients suffered TIA (TIA group) and 204 patients did not (control group). Hypertension (P = 0.037), diabetes (P = 0.026), homocysteine (Hcy)(P = 0.022), fasting blood glucose (P = 0.034), plaque properties (P = 0.000), luminal stenosis rate (P = 0.000), and proximal end WSS (P = 0.000) were independent influencing factors for TIA during follow-up. The accuracy of each indicator for predicting TIA individually was not high (area under the curve [AUC]< 0.9). The accuracy of the combined indicator including WSS (AUC = 0.944) was significantly higher than that of the combined indicator without WSS (AUC = 0.856) in predicting TIA (z = 2.177, P = 0.030). The sensitivity and specificity of the combined indicator including WSS were 86.67% and 92.16%, respectively. CONCLUSION WSS at plaque surface combined with hypertension, diabetes, Hcy, blood glucose, plaque properties, and stenosis rate can significantly improve the accuracy of predicting TIA.