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中华脑血管病杂志(电子版) ›› 2025, Vol. 19 ›› Issue (03) : 198 -206. doi: 10.3877/cma.j.issn.1673-9248.2025.03.005

所属专题: 文献

论著

脑小血管病患者步态障碍及认知障碍与神经影像学特征的相关性
刘万虎1, 步玮2, 董玉娟1, 李文君1, 贾亚南1, 刘翠翠1, 任慧玲1,()   
  1. 1 050051 石家庄,河北医科大学第三医院神经内科
    2 050051 石家庄,河北医科大学第三医院神经外科
  • 收稿日期:2024-08-22 出版日期:2025-06-01
  • 通信作者: 任慧玲
  • 基金资助:
    河北省医学科学研究课题计划(20240198)

Correlation between gait impairment, cognitive impairment, and neuroimaging features in patients with cerebral small vessel disease

Wanhu Liu1, Wei Bu2, Yujuan Dong1, Wenjun Li1, Yanan Jia1, Cuicui Liu1, Huiling Ren,1()   

  1. 1 Department of Neurology, the Third Hospital of Hebei Medical University, Shijiazhuang 050051, China
    2 Department of Neurosurgery, the Third Hospital of Hebei Medical University, Shijiazhuang 050051, China
  • Received:2024-08-22 Published:2025-06-01
  • Corresponding author: Huiling Ren
引用本文:

刘万虎, 步玮, 董玉娟, 李文君, 贾亚南, 刘翠翠, 任慧玲. 脑小血管病患者步态障碍及认知障碍与神经影像学特征的相关性[J/OL]. 中华脑血管病杂志(电子版), 2025, 19(03): 198-206.

Wanhu Liu, Wei Bu, Yujuan Dong, Wenjun Li, Yanan Jia, Cuicui Liu, Huiling Ren. Correlation between gait impairment, cognitive impairment, and neuroimaging features in patients with cerebral small vessel disease[J/OL]. Chinese Journal of Cerebrovascular Diseases(Electronic Edition), 2025, 19(03): 198-206.

目的

分析脑小血管病(CSVD)患者步态障碍及认知障碍与其神经影像学特征的相关性。

方法

回顾性连续纳入河北医科大学第三医院神经内科自2023年4月至11月经神经影像学检查确诊为CSVD的患者140例,评估CSVD各影像学标志物并计算出CSVD总负荷得分。根据CSVD总负荷将入选患者分为轻度CSVD总负荷组(0~1分,61例)和重度CSVD总负荷组(2~4分,79例),根据蒙特利尔认知评估量表(MoCA)得分将患者分为认知障碍组(0~25分,105例)和认知正常组(26~30分,35例)。采用单因素分析(t检验和χ2检验)比较不同组别患者临床和影像学资料的差异,应用多重线性回归分析研究CSVD总负荷与步态及认知障碍之间的关系,通过多因素Logistic回归确定认知障碍的独立影响因素,同时采用受试者工作特征(ROC)曲线评价筛选出的独立影响因素对认知障碍的预测效能。

结果

与轻度CSVD总负荷组比较,重度CSVD总负荷组步速[(0.34±0.12)m/s vs(0.47±0.11)m/s]、步长[(0.39±0.13)m vs(0.45±0.10)m]、Tinetti步态与平衡功能量表(POMA)评分[(20.90±4.42 )分 vs(23.95±2.44)分]、MoCA评分[(20.46±5.07)分 vs(24.43±4.04)分]均较低,步宽[(0.16±0.06)m vs(0.13±0.06)m]、起立行走计时(TUG)测试[(17.84±9.10)s vs(12.69±4.06)s]较高,差异均具有统计学意义[t=6.166,P<0.001;t=3.054,P=0.003;t=4.849,P<0.001;t=5.013,P<0.001;t=-2.950,P=0.004;t=-4.115,P<0.001]。多重线性回归分析结果显示,在调整了年龄、日常生活活动能力(ADL)评分、高血压病后,CSVD总负荷与步速、步长、Tinetti POMA、MoCA呈负相关,CSVD总负荷与步宽、TUG呈正相关(P<0.05)。与认知正常组比较,认知障碍组患者的年龄[(67.00±8.83)岁 vs(63.34±8.38)岁]、同型半胱氨酸水平[(18.02±10.52)μmol/L vs(14.13±6.45)μmol/L]、中重度脑白质高信号比例(67.6% vs 28.6%)、微出血比例(44.8% vs 14.3%)、CSVD总负荷分数[(2.21±1.17)分 vs (1.23±1.09)分]较高,步速[(0.37±0.13)m/s vs(0.48±0.10)m/s]较低,差异均具有统计学意义[t=-2.149,P=0.033;t=-2.017,P=0.046;χ2=16.415,P<0.001;χ2=10.443,P=0.001;t=4.382,P<0.001;t=4.627,P<0.001]。多因素Logistic回归分析显示,调整了年龄、同型半胱氨酸水平等混杂因素后,重度CSVD总负荷(OR=1.714,95%CI:1.074~2.736,P<0.05)、步速下降(OR=0.954,95%CI:0.914~0.995,P<0.05)与发生认知功能障碍仍显著相关。ROC曲线分析结果显示,CSVD总负荷联合步速预测CSVD患者发生认知障碍的曲线下面积为0.779(95%CI:0.695~0.863),其预测认知障碍发生的效能最高。

结论

重度CSVD总负荷会导致CSVD患者发生步态及认知障碍,增加跌倒风险;CSVD总负荷联合步速可预测CSVD患者认知障碍的发生。

Objective

To investigate the correlations between gait impairment, cognitive impairment, and neuroimaging features in patients with cerebral small vessel disease (CSVD).

Methods

A total of 140 patients diagnosed with CSVD by neuroimaging examinations at the Department of Neurology, the Third Hospital of Hebei Medical University from April to November 2023 were retrospectively and consecutively enrolled. CSVD burden was quantified using established imaging markers (white matter hyperintensity, lacunes, cerebral microbleeds, enlarged perivascular spaces) and summed into a total score (range: 0-4). Participants were stratified by burden severity: mild (0-1, n=61) and severe (2-4, n=79). Based on the montreal cognitive assessment (MoCA) score, patients were divided into the cognitive-impaired group (0-25 points, n=105) and the cognitive-impaired group (26-30 points, n=35). Univariate analysis (t-test and χ2 test) was used to compare differences in clinical and imaging data between different groups. Multiple linear regression analysis was applied to investigate the associations between CSVD total burden and gait/cognitive impairment. Multivariate logistic regression was used to identify independent influencing factors for cognitive impairment. Receiver operating characteristic (ROC) curve analysis was employed to evaluate diagnostic performance of key predictors.

Results

Compared to the mild-burden patients the severe-burden patients exhibited significantly slower gait speed [(0.34±0.12) m/s vs (0.47±0.11) m/s, t=6.166, P<0.001], reduced stride length [(0.39±0.13) m vs (0.45±0.10) m, t=3.054, P=0.003], lower Tinetti performance-oriented mobility assessment (POMA) score [(20.90±4.42) vs (23.95±2.44), t=4.849, P<0.001], and worse MoCA score [(20.46±5.07) vs (24.43±4.04), t=5.013, P<0.001]. Conversely, they had significantly wider stride width [(0.16±0.06) m vs (0.13±0.06) m, t=-2.950, P=0.004] longer and timed up and go (TUG) test time [(17.84±9.10) s vs (12.69±4.06) s, t=-4.115, P<0.001]. Multiple linear regression analysis showed that after adjusting for age, activities of daily living (ADL) score, and hypertension, CSVD total burden was negatively correlated with gait speed, stride length, Tinetti POMA score, and MoCA score, and positively correlated with stride width and TUG time (all P<0.05). Compared with the cognitively normal group, the cognitive impairment group had significantly higher age [(67.00±8.83) years vs (63.34±8.38) years, t=-2.149, P=0.033], homocysteine levels [(18.02±10.52) μmol/L vs (14.13±6.45) μmol/L, t=-2.017, P=0.046], proportions of moderate-to-severe white matter hyperintensity (67.6% vs 28.6%, χ2=16.415, P<0.001), proportions of cerebral microbleeds (44.8% vs 14.3%, χ2=10.443, P=0.001), and CSVD total burden score [(2.21±1.17) vs (1.23±1.09), t=4.382, P<0.001]. They also had significantly lower gait speed [(0.37±0.13) m/s vs (0.48±0.10) m/s, t=4.627, P<0.001]. Multivariate logistic regression analysis showed that after adjusting for confounding factors such as age and homocysteine levels, severe CSVD total burden (OR=1.714, 95%CI: 1.074-2.736, P<0.05) and decreased gait speed (OR=0.954, 95%CI: 0.914-0.995, P<0.05) remained significantly associated with cognitive impairment. ROC curve analysis showed that the combination of CSVD total burden and gait speed had the highest predictive efficacy for cognitive impairment in CSVD patients, with an area under the curve (AUC) of 0.779 (95%CI: 0.695-0.863).

Conclusion

Severe CSVD burden leads to gait and cognitive impairment in CSVD patients, increasing fall risk. Integrating neuroimaging burden quantification with gait speed assessment provides a clinically viable strategy for early identification of cognitive impairment in CSVD patients.

图1 应用联影智能影像分析系统评估脑小血管病(CSVD)影像学标志物结果示例(A:输入MRI图像,B:输出分析后图像,VB-Net为算法) 注:WMH为白质高信号,EPVS为扩大的血管周围间隙,CMB为脑微出血,Lacune为腔隙,FLAIR为液体反转恢复序列,SWI为弥散加权成像
表1 轻度CSVD总负荷组与重度CSVD总负荷组的临床资料比较
项目 轻度CSVD总负荷组(n=61) 重度CSVD总负荷组(n=79) 统计值 P
男性[例(%)] 35(57.4) 49(62.0) χ2=0.310 0.578
年龄(岁,
x¯±s
64.33±8.02 67.44±9.23 t=2.094 0.038
体质量指数(kg/m2
x¯±s
25.34±3.41 25.07±2.75 t=-0.469 0.640
ADL评分(分,
x¯±s
90.50±13.36 83.42±17.68 t=-2.591 0.011
吸烟[例(%)] 21(34.4) 29(36.7) χ2=0.113 0.737
饮酒[例(%)] 20(32.8) 16(20.3) χ2=2.687 0.101
既往史
高血压病[例(%)] 44(72.1) 69(87.3) χ2=5.116 0.024
糖尿病[例(%)] 21(34.4) 24(26.6) χ2=0.258 0.611
冠心病[例(%)] 12(19.7) 20(25.3) χ2=0.622 0.430
既往卒中[例(%)] 27(44.3) 30(38.0) χ2=0.564 0.453
实验室检查
总胆固醇(mmol/L,
x¯±s
4.54±0.95 4.30±1.14 t=-1.324 0.188
甘油三酯(mmol/L,
x¯±s
1.76±1.10 1.54±0.89 t=-1.279 0.203
高密度脂蛋白胆固醇(mmol/L,
x¯±s
1.21±0.27 1.13±0.22 t=-1.861 0.065
低密度脂蛋白胆固醇(mmol/L,
x¯±s
2.73±0.79 2.50±0.88 t=-1.536 0.127
空腹血糖(mmol/L,
x¯±s
6.97±3.12 6.55±2.72 t=-0.850 0.397
同型半胱氨酸(μmol/L,
x¯±s
16.78±9.25 17.07±10.10 t=0.160 0.873
影像学资料
lacune[例(%)] 8(13.1) 62(78.5) χ2=58.830 <0.001
CMB[例(%)] 6(9.8) 46(58.2) χ2=34.526 <0.001
基底节区中重度EPVS[例(%)] 15(26.2) 57(70.9) χ2=31.172 <0.001
中重度WMH[例(%)] 19(31.1) 62(78.5) χ2=31.629 <0.001
表2 不同CSVD总负荷组步态及认知功能的比较(
x¯±s
表3 脑小血管病总负荷与步态及认知功能的多重线性回归分析结果
表4 不同认知功能组CSVD患者的一般临床资料比较
项目 认知障碍组(n=105) 认知正常组(n=35) 统计值 P
男性[例(%)] 65(61.9) 19(54.3) χ2=0.635 0.426
年龄(岁,
x¯±s
67.00±8.83 63.34±8.38 t=-2.149 0.033
体质量指数(kg/m2
x¯±s
25.27±3.07 24.97±3.04 t=-0.456 0.649
ADL评分(分,
x¯±s
85.67±16.89 88.97±14.24 t=1.028 0.306
吸烟[例(%)] 38(36.1) 12(35.4) χ2=0.058 0.810
饮酒[例(%)] 26(36.2) 10(28.6) χ2=0.174 0.677
既往史
高血压病[例(%)] 87(82.9) 26(74.3) χ2=1.239 0.226
糖尿病[例(%)] 31(29.5) 14(40.0) χ2=1.321 0.250
冠心病[例(%)] 26(24.8) 6(17.1) χ2=0.864 0.353
既往卒中[例(%)] 43(41.0) 14(40.0) χ2=0.010 0.921
实验室检查
总胆固醇(mmol/L,
x¯±s
4.34±1.10 4.59±0.96 t=1.185 0.238
甘油三酯(mmol/L,
x¯±s
1.57±0.91 1.85±1.18 t=1.469 0.144
高密度脂蛋白胆固醇(mmol/L,
x¯±s
1.16±0.25 1.16±0.23 t=-0.071 0.944
低密度脂蛋白胆固醇(mmol/L,
x¯±s
2.55±0.87 2.77±0.76 t=1.304 0.195
空腹血糖(mmol/L,
x¯±s
6.78±3.15 6.59±2.02 t=-0.330 0.742
同型半胱氨酸(μmol/L,
x¯±s
18.02±10.52 14.13±6.45 t=-2.017 0.046
影像学资料
lacune[例(%)] 55(52.4) 15(42.8) χ2=0.952 0.329
CMB[例(%)] 47(44.8) 5(14.3) χ2=10.443 0.001
基底节区中重度EPVS[例(%)] 59(56.2) 13(37.1) χ2=3.813 0.051
中重度WMH[例(%)] 71(67.6) 10(28.6) χ2=16.415 <0.001
CSVD总负荷(分,
x¯±s
2.21±1.17 1.23±1.09 t=4.382 <0.001
步态参数
步速(m/s,
x¯±s
0.37±0.13 0.48±0.10 t=-4.627 <0.001
步长(m,
x¯±s
0.40±0.13 0.45±0.10 t=-1.877 0.063
步宽(m,
x¯±s
0.15±0.06 0.14±0.06 t=-1.092 0.277
表5 CSVD患者发生认知障碍的多因素Logistic回归分析
表6 CSVD总负荷、步速对CSVD患者发生认知障碍的预测价值
图2 步速及CSVD总负荷预测CSVD患者发生认知障碍的受试者工作特征曲线 注:CSVD为脑小血管病
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