多个血清生物标志物和脑血管之间的关联在患有动脉瘤下关节出血的患者中
Chenghao Yang1, Fei Luo1, Xi Chen1
1Department of Neurosurgery, Zigong Fourth People's Hospital, Zigong, Sichuan, China.
Frontiers in neurology
|June 20, 2025
概括
血清生物标志物如HIF-1α,VEGF和ET-1,以及格拉斯哥昏迷量表得分,可以预测动脉瘤下关节出血 (aSAH) 患者的脑血管 (CVS). 这有助于早期识别高风险个体.
科学领域:
- 神经学 神经学
- 生物标志物研究 生物标志物研究
- 关键护理医学 关键护理医学
背景情况:
- 大脑血管 (CVS) 是神经瘤下关节出血 (aSAH) 后的一个严重并发症.
- CVS显著增加了aSAH患者的残疾和死亡风险.
- 早期预测CVS对于及时干预至关重要.
研究的目的:
- 为了确定预测aSAH患者CVS发展的血清生物标志物.
- 评估这些生物标志物和CVS临床因素的预测准确性.
- 在aSAH中开发CVS早期风险分层的预测模型.
主要方法:
- 从2020年1月到2023年12月对175名aSAH患者的回顾性分析.
- 在手术后24小时收集基线信息和血清生物标志物.
- 单变量和多变量物流回归分析以确定风险因素并构建预测模型.
主要成果:
- 确定了四种CVS的独立预测因素:格拉斯哥昏迷量表 (GCS) 评分,缺氧诱导因子-1α (HIF-1α),血管内皮生长因子 (VEGF) 和内皮素-1 (ET-1).
- 结合这些因素的预测模型实现了高准确性 (随机森林的AUC为0.966,后勤回归为0.959).
- HIF-1α,VEGF和ET-1与心血管系统发展有显著的关联 (分别p < 0.001,p = 0.001,p = 0.035).
结论:
- 在aSAH患者中,GCS得分,HIF-1α,VEGF和ET-1都是CVS的可靠预测指标.
- 开发的预测模型在早期CVS风险识别方面表现出了显著的准确性.
- 这种工具可以帮助临床医生管理高风险患心血管疾病的aSAH患者.
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