Neurosonological Parameters May Predict the Risk of Cerebral Hyperperfusion Syndrome After Carotid Artery Stenting

Abstract

Cerebral hyperperfusion syndrome (CHS) is a critical complicationin patients underwent carotid artery stenting (CAS). We sought to explore neurosonological parameters and additional risk factors associated with CHS in patients following CAS and further to develop a prediction model for CHS after CAS. A total of 197 patients who underwent CAS were included in this observational study. All patients were divided into CHS and non-CHS groups. Demographic, clinical, treatment, and laboratory data were extracted from electronic medical records. Logistic regression analysis and nomogram listing were used to build a CHS prediction model. Machine learning algorithms with five-fold cross-validation were used to further validate the CHS prediction model. Twenty-two patients had clinically manifested CHS. Four parameters were detected as risk factors associated with CHS, including effective collateral circulation (ECC) (p = 0.046), asymmetry ratio of peak systolic velocity of the middle cerebral artery (ARP) (p = 0.001), severe stenosis or occlusion of the contralateral carotid artery (p = 0.010), and low-density lipoprotein cholesterol (LDL-C) (P = 0.025). The area under the curve for the prediction model of CHS in the cohort was 0.835 (95% CI 0.760-0.909). In this study, CHS following CAS was associated with ECC, ARP, contralateral ICA severe stenosis or occlusion, as well as LDL-C. Subsequently, the CHS prediction model for CAS was built, which has the potential to facilitate tailored and precise management as well as treatment strategies for patients at high risk of CHS.