中国现代神经疾病杂志 ›› 2025, Vol. 25 ›› Issue (5): 396-402. doi: 10.3969/j.issn.1672-6731.2025.05.006

• 脑血管病临床研究 • 上一篇    下一篇

2 小动脉硬化型脑小血管病总负荷与非高密度脂蛋白胆固醇相关性研究

王春雨, 董爱勤*(), 王文慧, 张海柳   

  1. 061000 河北省沧州市中心医院神经内科
  • 收稿日期:2025-03-27 出版日期:2025-05-25 发布日期:2025-06-05
  • 通讯作者: 董爱勤
  • 基金资助:
    河北省医学科学研究课题计划(20251554)

Study on the relationship between the total burden of arteriosclerotic cerebral small vessel disease and non-high-density lipoprotein cholesterol

Chun-yu WANG, Ai-qin DONG*(), Wen-hui WANG, Hai-liu ZHANG   

  1. Department of Neurology, Cangzhou Central Hospital, Cangzhou 061000, Hebei, China
  • Received:2025-03-27 Online:2025-05-25 Published:2025-06-05
  • Contact: Ai-qin DONG
  • Supported by:
    Medical Science Research Project of Hebei(20251554)

摘要:

目的: 初步探讨血清非高密度脂蛋白胆固醇(non-HDL-C)与脑小血管病总负荷的相关性,并筛查脑小血管病总负荷严重程度的影响因素。方法: 纳入2024年12月至2025年2月河北省沧州市中心医院诊断与治疗的166例小动脉硬化型脑小血管病(aCSVD)患者,采用MRI分析脑白质高信号、腔隙性梗死、脑微出血和扩大的血管周围间隙4种脑小血管病影像学标志物,计算脑小血管病总负荷评分。Spearman秩相关分析探讨血清non-HDL-C水平与脑小血管病总负荷评分的相关性,单因素和多因素Logistic回归分析筛查脑小血管病总负荷严重程度的影响因素。结果: 共166例aCSVD患者根据脑小血管病总负荷评分分为轻度总负荷(0 ~ 1分)组(79例)和中重度总负荷(2 ~ 4分)组(87例)。Spearman秩相关分析显示,non-HDL-C水平与脑小血管病总负荷评分呈正相关(rs = 0.184,P = 0.018)。Logistic回归分析显示,年龄增长(OR = 1.046,95%CI:1.001 ~ 1.094;P = 0.045)、同型半胱氨酸水平较高(OR = 1.057,95%CI:1.003 ~ 1.115;P = 0.040)和non-HDL-C水平较高(OR = 1.376,95%CI:1.026 ~ 1.846;P = 0.033)是中重度脑小血管病总负荷的危险因素。结论: 血清non-HDL-C水平与脑小血管病总负荷评分呈正相关,且是中重度脑小血管病总负荷的危险因素,有望成为aCSVD的潜在干预靶点。

关键词: 大脑小血管疾病, 小动脉硬化, 胆固醇,HDL, 危险因素, Logistic模型

Abstract:

Objective: A preliminary study on the correlation between serum non - high - density lipoprotein cholesterol (non - HDL - C) and the severity of total burden of cerebral small vessel disease (CSVD), and influencing factors of the severity of CSVD total burden were screened. Methods: A total of 166 patients diagnosed with arteriosclerotic CSVD (aCSVD) admitted to Cangzhou Central Hospital from December 2024 to February 2025 were retrospectively enrolled. We evaluated white matter hyperintensity (WMH), lacunar infarct (LACI), cerebral microbleeds (CMBs) and enlarged perivascular space (EPVS) based on the cranial MRI to calculate the CSVD total burden score. Spearman rank correlation analysis was performed to analyse the relationship between non - HDL - C and CSVD total burden. Univariate and multivariate Logistic regression analyses were further used to identify influencing factors for the severity of CSVD total burden. Results: According to the CSVD total burden score, the patients were divided into the mild total burden (0-1 point) group (n = 79) and the moderate and severe total burden (2-4 points) group (n = 87). There was a positive correlation between non - HDL - C level and CSVD total burden score (rs = 0.184, P = 0.018). Logistic regression analysis revealed that older age (OR = 1.046, 95%CI: 1.001-1.094; P = 0.045), increased homocysteine (OR = 1.057, 95%CI: 1.003-1.115; P = 0.040) and increased non-HDL-C (OR = 1.376, 95%CI: 1.026-1.848; P = 0.033) were risk factors for the moderate and severe CSVD total burden. Conclusions: Increased non - HDL - C is a risk factor for the moderate and severe CSVD total burden, or it may potentially serve as an target of intervention for aCSVD.

Key words: Cerebral small vessel diseases, Arteriolosclerosis, Cholesterol, HDL, Risk factors, Logistic models