Association Between Carotid Atherosclerosis and Post-Stroke Cognitive Impairment in Patients With Mild Ischemic...

Post-stroke cognitive impairment (PSCI) is a common yet frequently overlooked complication that adversely affects recovery and long-term outcomes in stroke survivors. Early identification of individuals at risk is essential for timely cognitive rehabilitation.

This study aimed to investigate the association between carotid atherosclerosis indicators-specifically, carotid plaque burden and degree of carotid artery stenosis-and the occurrence of PSCI in patients with mild acute ischemic stroke (AIS), using carotid ultrasound as a cost-effective, widely accessible diagnostic modality.

A prospective cohort of 181 patients diagnosed with AIS within 7 days of onset was enrolled. Baseline demographics, clinical characteristics, and carotid ultrasound parameters were collected. PSCI was assessed at 6 months using the Montreal Cognitive Assessment (MoCA). Binary logistic regression was used to identify independent predictors of PSCI. The predictive accuracy of individual and combined markers was evaluated using receiver operating characteristic (ROC) curve analysis.

Among 181 participants, 75 (41.4%) were diagnosed with PSCI at the 6-month follow-up. Multivariate analysis revealed that the carotid plaque Crouse score (OR = 1.157, 95% CI: 1.055-1.269) and severe carotid artery stenosis (OR = 3.733, 95% CI: 1.582-8.811) were independently associated with PSCI. ROC analysis demonstrated modest predictive performance for the Crouse score (AUC = 0.667) and stenosis (AUC = 0.596), while a multivariable model incorporating clinical and ultrasound parameters achieved an AUC of 0.818 (95% CI: 0.758-0.877). Significant between-group differences were observed in AVLT-I, AVLT-II, VFT, TMT-B, CDT, and MoCA subdomains (p < 0.05).

Carotid plaque burden and severe carotid stenosis are independently associated with the development of PSCI in patients with mild AIS. Carotid ultrasound, combined with clinical risk factors, may provide a practical approach for early identification and risk stratification of PSCI.

Chinese Clinical Trial Registry (ChiCTR1900022675); URL: https://www.chictr.org.cn/.