一个时间序列聚类分析的诱导后血压轨迹
Maxim Glebov1,2, Maksim Katsin1, Haim Berkenstadt1,3
1Department of Anesthesiology, Sheba Medical Center, Ramat Gan, Israel.
Scientific reports
|January 16, 2026
概括
通用麻醉诱导会导致各种血压变化. 这项研究在患者中确定了五种不同的平均动脉压模式,有助于在手术期间个性化血液动力学管理.
科学领域:
- 麻醉学 麻醉学
- 心血管生理学心血管生理学
- 数据科学在医学中的数据科学
背景情况:
- 诱导全身麻醉经常导致显著的血液动力学变化,特别是血压 (BP) 的波动.
- 这些早期的诱导后血压变化在患者之间表现出相当大的变化,并可能导致外科手术后并发症.
- 目前用于管理诱导后血压的临床策略是反应性的,可能无法有效地解决个体患者的差异.
研究的目的:
- 为了确定一般麻醉诱导后的前10分钟内平均动脉压 (MAP) 响应的明显模式.
- 应用时间序列聚类方法来表征MAP轨迹.
- 分析与不同MAP反应模式相关的患者特征.
主要方法:
- 对17,645名接受非心脏和非产科手术的成年患者进行了回顾性队列研究.
- 在1分钟间隔通过侵入性动脉线或非侵入性袖口收集的血压数据.
- 无监督的X-means集群与动态时间扭曲用于识别MAP轨迹模式.
主要成果:
- 确定了五种不同的MAP轨迹:初始下降-高原 (31.8%),逐渐中度下降 (18.4%),初始下降-恢复 (7.5%),逐渐严重下降 (29.6%) 和初始下降-低高原 (12.7%).
- 在基线MAP,并发症概况和抗高血压药物使用中观察到跨集群的显著差异.
- 麻醉剂剂量差异在统计上显著,但在临床上没有意义.
结论:
- 可以使用时间序列集群识别明显的诱导后BP轨迹.
- 这些已识别的模式为理解和潜在地预测个体患者对麻醉诱导的血液动力学反应提供了一个框架.
- 根据更丰富的临床数据进行进一步验证是有必要的,以完善个性化的术后血液动力学管理.
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