Observational Study
Copyright ©The Author(s) 2019. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Cases. Sep 26, 2019; 7(18): 2722-2733
Published online Sep 26, 2019. doi: 10.12998/wjcc.v7.i18.2722
Wall shear stress can improve prediction accuracy for transient ischemic attack
Qiu-Yun Liu, Qi Duan, Xiao-Hong Fu, Mei Jiang, Hong-Wei Xia, Yong-Lin Wan
Qiu-Yun Liu, Xiao-Hong Fu, Hong-Wei Xia, Yong-Lin Wan, Department of Ultrasound, Naval Military Medical University Affiliated Gongli Hospital, Shanghai 200000, China
Qi Duan, Department of Ultrasound, Shanghai Hemujia Hospital, Shanghai 200000, China
Mei Jiang, Department of Neurology, Naval Military Medical University Affiliated Gongli Hospital, Shanghai 200000, China
Author contributions: Liu QY, Duan Q, Fu XH, Jiang M, and Xia HW designed the research; Liu QY, Duan Q, Fu XH, and Wan YL performed the research; Liu QY, Duan Q, and Xia HW contributed new analytic tools; Liu QY and Xia HW analyzed the data; and Liu QY, Duan Q, Fu XH, Jiang M, Xia HW, and Wan YL wrote the paper.
Supported by Shanghai Health and Family Planning Commission, No. 201440051; Shanghai Pudong New Area Health and Family Planning Commission, No. PW2016A-19.
Institutional review board statement: The study was approved by the ethics committee of Naval Military Medical University Affiliated Gongli Hospital.
Informed consent statement: All patients gave informed consent.
Conflict-of-interest statement: The authors declare that they have no competing interests.
Data sharing statement: No additional data are available.
STROBE statement: The authors have read the STROBE Statement, and the manuscript was prepared and revised according to the STROBE Statement.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Corresponding author: Duan Qi, MD, Chief Doctor, Department of Ultrasound, Shanghai Hemujia Hospital, No. 1139, Changning District, Shanghai 200336, China. chen_qingan@163.com
Telephone: +86-21-22163999
Received: May 18, 2019
Peer-review started: May 21, 2019
First decision: July 30, 2019
Revised: August 5, 2019
Accepted: August 20, 2019
Article in press: August 20, 2019
Published online: September 26, 2019
Processing time: 130 Days and 2.1 Hours
Abstract
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.

Keywords: Transient ischemic attack; Acute ischemic stroke; Wall shear stress; Atherosclerosis; Plaque

Core tip: Early prediction of transient ischemic attack (TIA) is of great importance. However, the accuracy of the predicted methods including clinical, biochemical, and imaging indicators related to carotid atherosclerosis is limited. The purpose of this study was to explore the role of combining wall shear stress (WSS) with conventional predictive indicators in improving the accuracy of TIA prediction. Our study indicated that the WSS at plaque surface combined with traditional indicators such as hypertension, diabetes, Hcy, blood glucose, plaque properties, and stenosis rate can significantly improve the accuracy of predicting TIA.