国家神经系统疾病临床医学研究中心数据管理与共享系统

发表杂志：Curr Neurovasc Res

发表类型: Article

影响因子(IF): 2.294

PMID: 39069699 Pubmed原文链接 全文下载

Intracranial atherosclerosis (ICAS) is a major cause of ischemic stroke worldwide. Patients affected by this disease have a high risk of suffering further ischemic strokes and other major vascular events despite the best medical therapy available. However, identification of factors that characterize a high-risk ICAS patient is a clinical problem that is yet to be solved. Inflammation is known to play a crucial role in all the stages of atherosclerosis affecting extracranial arterial beds but its role in ICAS is not firmly established. In this article, we aimed to investigate the relationship between inflammatory biomarkers and incidence, distribution and prognosis of ICAS. We try to find out the most reliable biomarker to predict the stroke recurrent risk at one year for patients with ICAS, and explore the threshold of the biomarker. The results of this study would provide a theoretical basis for inflammation targeted treatment strategies in the future.

Patients with complete data of inflammatory biomarkers in CNSR-III were recruited in this subgroup analysis. Intracranial artery lesions were assessed by three-dimensional time of flight magnetic resonance angiography (3D TOF MRA), computed tomography angiography (CTA) or Digital subtraction angiography (DSA). The degree of intracranial artery stenosis was calculated using the Warfarin-Aspirin Symptomatic Intracranial Disease (WASID) criteria. The extracranial part of internal carotid artery was estimated with ultrasonographic examination according to the published diagnostic criteria or by contrast-enhanced MRA (CEMRA), aortic arch & neck CTA, or DSA. The North American Symptomatic Carotid Endarterectomy Trial (NASCET) criteria were adopted in adjudicating the stenosis of extra-cranial artery stenosis (ECAS). Statistical significance for intergroup differences was assessed by the x2 test for categorical variables and the Student t-test, Mann–Whitney U test, and Kruskal–Wallis test for continuous variables. Inflammatory biomarkers were not normally distributed (Kolmogorov–Smirnov). The Spearman coefficient was used to study the correlation between the extent of ICAS and inflammatory biomarkers level. Using multivariate logistic regression analysis, we computed age-, sex- and vascular risk factor–adjusted odds ratios (ORs) for a greater extent of ICAS associated with increasing quartiles of the distribution of inflammatory biomarkers, with the lowest quartile as the reference. A multiple logistic regression model was performed to identify independent markers of a greater extent of ICAS, in which variables showing a p value of <0.1 on univariate testing were included, and adjustment for age, sex, and vascular risk factors was conducted. For inflammatory biomarkers’ level, a receiver operator characteristic (ROC) curve was configured, and optimal cutoff values were used to include the variable into the regression model. Results were expressed as adjusted ORs and corresponding 95% CIs. A p value of <0.05 was considered significant.