河北医科大学学报 ›› 2025, Vol. 46 ›› Issue (5): 514-519.doi: 10.3969/j.issn.1007-3205.2025.05.004

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血压变异性与穿支动脉粥样硬化病早期神经功能恶化的相关性分析

  

  1. 航天中心医院神经内科,北京 100049

  • 出版日期:2025-05-25 发布日期:2025-05-23
  • 作者简介:朱慧(1990-),女,山东德州人,航天中心医院主治医师,医学硕士,从事脑血管疾病诊治研究。

Correlation between blood pressure variability and early neurological deterioration in patients with branch atheromatous disease

  1. Department of Neurology, Aerospace Central Hospital, Beijing 100049, China

  • Online:2025-05-25 Published:2025-05-23

摘要: 目的 探讨血压变异性(blood pressure variability,BPV)与穿支动脉粥样硬化病(branch atheromatous disease,BAD)早期神经功能恶化(early neurological deterioration,END)的相关性。
方法 连续性纳入2022年1月—2023年6月于航天中心医院住院的200例BAD患者,记录入院第1~3天、第7天美国国立卫生研究院卒中量表(National Institutes of Health Stroke Scale, NIHSS)评分,根据NIHSS评分增幅分为END组(69例)和非END组(131例),记录2组基本资料、梗死部位,实验室指标、血压变异参数,2组间影响因素分析采用t检验、Logistic回归分析。采用受试者工作特征(receiver operator characteristic,ROC)曲线下面积(area under curve,AUC)分析BPV指标对END的诊断价值。
结果 2组空腹血糖、总胆固醇、低密度脂蛋白及梗死部位、夜间平均收缩压(night mean systolic blood pressure,NMSBP)、夜间平均舒张压(night mean diastolic blood pressure,NMDBP)、24 h收缩压标准差(24 hours systolic blood pressure standard deviation,24 hSBP-SD)、日间收缩压标准差(day systolic blood pressure standard deviation,DSBP-SD)、夜间收缩压标准差(night systolic blood pressure standard deviation,NSBP-SD)、24 h舒张压标准差(24 hours diastolic blood pressure standard deviation,24 hDBP-SD)、日间舒张压标准差(day diastolic blood pressure standard deviation,DDBP-SD)、夜间舒张压标准差(night diastolic blood pressure standard deviation,NDBP-SD)、日间收缩压变异系数(day systolic blood pressure CV,DSBP-CV)、夜间收缩压变异系数(night systolic blood pressure CV,NSBP-CV)、24 h〖KG*5〗舒张压变异系数(24 hours diastolic blood pressure CV,24 hDBP-CV)和日间舒张压变异系数(day diastolic blood pressure CV,DDBP-CV)比较,差异均有统计学意义(P<0.05);Logistic回归分析显示DSBP-SD、NSBP-SD、DDBP-CV是END的危险因素(P<0.05);ROC曲线显示,血压变异联合指标诊断的AUC=0.746,特异度和敏感度分别为0.817和0.609。
结论 BAD患者易发生END,BPV是重要的影响因素,可一定程度预测END的发生。BPV指标监测为疾病诊疗提供新思路。


关键词: 动脉粥样硬化, 血压变异, 血压监测

Abstract: Objective To analyze the association between blood pressure variability (BPV)  and early neurological deterioration (END) in patients with branch atheromatous disease (BAD). 
Methods A total of 200 BAD patients were consecutively enrolled in Aerospace Central Hospital from Jan. 2022 to Jun. 2023, and National Institutes of Health Stroke Scale (NIHSS) score at 1 d, 3 d, and 7 d after admission were recorded. According to the increase in NIHSS score, they were divided into END (n=69) and non-END groups (n=131). The basic data, infarct site,laboratory indicators, and BPV were recorded. The influencing factors between two groups was analyzed using t-test and Logistic regression analysis. The area under receiver operator characteristic (ROC) curve (AUC) was used to analyze the diagnostic value of BPV indicators for END. 
Results The fasting blood glucose, total cholesterol, low-density lipoprotein, infarct site, night mean systolic blood pressure (NMSBP),  night mean diastolic blood pressure (NMDBP), 24 hours systolic blood pressure standard deviation (24 hSBP-SD), day systolic blood pressure standard deviation(DSBP-SD), night systolic blood pressure standard deviation (NSBP-SD), 24 hours diastolic blood pressure standard deviation (24 hDBP-SD), day diastolic blood pressure standard deviation (DDBP-SD), night diastolic blood pressure standard deviation (NDBP-SD), day systolic blood pressure CV (DSBP- CV), night systolic blood pressure CV (NSBP- CV), 24 hours diastolic blood pressure CV (24 hDBP-CV), and day diastolic blood pressure CV (DDBP-CV) were compared between the two groups, showing significant differences (P<0.05). T test, Logistic regression analysis and ROC curve were applied to statistical analysis. Logistic regression analysis showed that DSBP-SD, NSBP-SD, and DDBP-CV were independent risk factors for END in BAD patients (P<0.05). The ROC curve revealed that the AUC of joint indicators of BPV was 0.746, and the specificity and sensitivity were 0. 817 and 0.609 respectively. 
Conclusion Patients with BAD are subjected to END, and BPV is an important influencing factor, which can predict the occurrence of END. The monitoring of BPV provides a new idea for disease diagnosis and treatment. 


Key words: atherosclerosis, blood pressure variability, blood pressure monitoring