Cerebral microbleed burden is associated with domain-specific cognitive impairment pattern in acute stroke

医学 认知障碍 急性中风 认知 冲程(发动机) 心脏病学 内科学 物理医学与康复 领域(数学分析) 认知评估系统 缺血性中风 神经影像学 疾病 听力学 蒙特利尔认知评估
作者
Yun-He Xia,Xiao Hu,Sun-hong Yan,Zi-Jie Wang,Fang-Jian Zhu,Chu Chen,Jin Li,Yue Sun,Chuanqin Fang,Qi Li
出处
期刊:Neurological Research [Taylor & Francis]
卷期号:: 1-9
标识
DOI:10.1080/01616412.2026.2621223
摘要

Objective Cerebral microbleeds (CMBs) represent a key imaging marker of cerebral small vessel disease (CSVD). This study aimed to investigate the relationship between CMB burden and domain-specific cognitive impairment in acute stroke patients.Methods We enrolled 163 acute stroke patients stratified by Montreal Cognitive Assessment (MoCA) scores into cognitively impaired (MoCA ≤22, n = 79) and preserved (MoCA > 22, n = 84) groups. Demographic, clinical, laboratory, and neuroimaging data were collected. Multivariable logistic regression was used to identify factors associated with global cognitive impairment, while linear regression models were applied to evaluate the associations between CMB burden and specific cognitive domains.Results Patients with cognitive impairment were older, less educated, and exhibited a higher CSVD burden (all p < 0.05). In multivariate analyses, only age was independently associated with global cognitive impairment (OR = 1.082, p = 0.002). However, linear regression revealed that total CMB number was inversely correlated with visuospatial/executive function (β = −0.156) and memory recall (β = −0.201) after adjustment for confounding factors. Location-specific analysis demonstrated that mixed CMBs (involving both lobar and deep regions) were independently associated with visuospatial/executive deficits (β = −0.255), while deep CMBs specifically impacted abstract reasoning (β = −0.220).Conclusion CMB burden, particularly mixed and deep distributions, is independently associated with specific cognitive domain impairments in acute stroke patients, highlighting the importance of CMB assessment for cognitive risk stratification.
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