Wall shear stress can improve prediction accuracy for transient ischemic attack

Area of Science:

• Cardiovascular Medicine
• Neurology
• Medical Imaging
• Biomedical Engineering

Background:

• Early prediction of transient ischemic attack (TIA) is crucial for clinical management.
• Existing prediction models using clinical, biochemical, and imaging indicators for TIA lack sufficient accuracy.
• Carotid atherosclerosis is a significant risk factor for TIA.

Purpose of the Study:

• To investigate the utility of combining wall shear stress (WSS) with conventional indicators for enhanced TIA prediction.
• To assess the diagnostic accuracy of WSS in predicting TIA in patients with carotid atherosclerosis.

Main Methods:

• Recruited 250 patients with atherosclerosis undergoing carotid ultrasonography.
• Measured plaque characteristics, stenosis, and calculated WSS using specialized software.
• Followed patients for 4 years, analyzing clinical, biochemical, and ultrasound data using logistic regression and ROC curves.

Main Results:

• Hypertension, diabetes, homocysteine (Hcy), fasting blood glucose, plaque properties, stenosis rate, and proximal end WSS were independent TIA predictors.
• Combined WSS with conventional factors yielded a higher prediction accuracy (AUC = 0.944) compared to conventional factors alone (AUC = 0.856).
• The combined model demonstrated high sensitivity (86.67%) and specificity (92.16%) for TIA prediction.

Conclusions:

• Wall shear stress (WSS) at the plaque surface is a valuable independent predictor of TIA.
• Combining WSS with clinical factors (hypertension, diabetes), biochemical markers (Hcy, blood glucose), and imaging features (plaque properties, stenosis) significantly improves TIA prediction accuracy.
• This integrated approach offers a more robust tool for early TIA risk assessment in patients with carotid atherosclerosis.