脑出血与脑小血管病亚型及总负荷的关系研究

目的 探讨自发性脑出血的严重程度与脑小血管病（cerebral small vessel disease，CSVD）各亚型及总 负荷之间的关系。 方法 回顾性分析2013年8月-2017年8月于河南科技大学第一附属医院就诊的发病24 h内住院的 脑出血患者的临床资料。根据患者入院24 h内、3～5 d、10～14 d头颅CT检查结果及头颅MRI检查结 果，计算不同时间段血肿及水肿体积，评估腔隙（lacune，LA）、白质高信号（white matter hyperintensity， WMH）、扩大的血管周围间隙（enlarged perivascular space，ePVS）、脑微出血（cerebral microbleed，CMB） 的严重程度并计算总CSVD评分，分析脑出血的严重程度与CSVD各亚型及总负荷的关系。 结果 最终共纳入85例脑出血患者，其中脑叶出血33例（38.82%），深部出血52例（61.18%）。校正 年龄、平均动脉压、入院GCS评分、入院NIHSS评分后，在血肿体积的多元线性回归模型中，CMB数目与 不同时期血肿体积均正相关，WMH的Fazekas评分与不同时期血肿体积均负相关；校正年龄、平均动 脉压、入院GCS评分、入院NIHSS评分、血肿体积后，在水肿体积的多元线性回归模型中，ePVS与不同 时期水肿体积均呈负相关。CSVD总负荷与不同时期血肿体积均不相关，与入院24 h内水肿体积不相 关，与3～5 d、10～14 d水肿体积负相关。 结论 CMB数目越多，WMH的Fazekas评分越低，血肿体积越大。ePVS的存在可能是脑出血后水肿程 度较轻的标志；CSVD总负荷可以预测3～14 d脑水肿的严重程度。

Relationship Between Cerebral Hemorrhage and Subtypes and Total Burden of Cerebral Small Vessel Diseases

Objective To investigate the relationship between cerebral hemorrhage and the subtypes and the
total burden of cerebral small vessel disease (CSVD) in patients with spontaneous intracerebral
hemorrhage (ICH).
Methods A retrospective analysis of patients with spontaneous ICH within 24 h after onset from
the First Affiliated Hospital of Henan University of Science and Technology from August 2013 to
August 2017 were performed. Based on the results of head CT and MRI within 24h after admission,
day 3-5 and day 10-14, the hematoma volume and edema volume at different periods after onset
were calculated, and the severity of lacunes (LA), white matter hyperintensity (WMH), enlarged
perivascular space (ePVS), cerebral microbleeds (CMBs) and the total burden of CSVD were
assessed. The relationship between cerebral hemorrhage and the subtypes of CSVD and the total
burden of CSVD were analyzed.
Results A total of 85 eligible patients were included, with lobar hemorrhage in 33 (38.82%) cases
and deep hemorrhage in 52 (61.18%) cases. After adjustment for age, mean arterial blood pressure,
GCS and NIHSS score at admission, the multivariable linear regression model of hematoma volumeshowed that the number of CMBs was positively correlated with hematoma volume, the Fazekas
score was negatively correlated with hematoma volume. After adjustment for age, mean arterial
blood pressure, GCS and NIHSS score at admission and hematoma volume, the multivariable linear
regression model of edema volume showed that ePVS was negatively correlated with edema volume.
The total burden of CSVD was not correlated with hematoma volume in different periods as well as
the perihematomal edema volume within 24 hours after ICH, whereas it was negatively correlated
with the edema volume at day 3-14.
Conclusions Hematoma expanded with the increase of CMBs number and the decrease of Fazekas
score. The presence of ePVS may be a sign of mild perihematomal edema. The total burden of
CSVD can predict the severity of perihematomal edema at day 3-14 after ICH.