在神经临床护理中无监督集群:系统性审查
Jeanette Tas1,2, Verena Rass3, Bogdan-Andrei Ianosi4,5
1Department of Neurology, Kepler University Hospital, Johannes Kepler University Linz, Linz, Austria. tasjeanette@gmail.com.
Neurocritical care
|November 19, 2024
概括
无监督集群有助于分析复杂的神经关键护理数据,识别患者子组,并改善对TBI等急性脑损伤的结果预测. 这种方法有助于诊断和理解疾病病理生理学.
科学领域:
- 神经临界护理是指神经临界护理.
- 数据科学数据科学数据科学
- 生物医学信息学 生物医学信息学
背景情况:
- 神经临界护理 (NCC) 由于技术进步和多样化的数据流而面临复杂性.
- 需要创新的方法来理解急性脑损伤中记录的变量之间的相互作用.
- 无监督集群提供了一种方法来整合各种数据流以提供临床支持.
研究的目的:
- 系统地审查在神经临床护理 (NCC) 研究中无监督聚类的应用.
- 在急性脑损伤患者数据中提供聚类应用的概述.
- 讨论在NCC中使用无监督集群的未来研究的考虑因素.
主要方法:
- 在2024年3月13日之前对Medline,Scopus和Web of Science数据库进行系统审查.
- 包括的研究集中在急性脑损伤 (TBI,SAH,ICH,AIS,HI-BI) 的无监督集群.
- 遵守系统审查和元分析 (PRISMA) 准则的首选报告项目.
主要成果:
- 在NCC中确定了18项使用无监督聚类的研究,主要是对创伤性脑损伤 (TBI) 患者 (12/18).
- 通常使用的数据包括人口统计,临床和监测数据,其中内压力很常见 (8/18).
- 在12项研究中的9项中,无监督集群确定了用于临床结果的新型表型,采用了各种集群方法.
结论:
- 无监督的集群有效地将神经临界护理患者的表型,特别是TBI患者,跨越疾病阶段.
- 这种方法可以识别预后的患者集群,从而有可能改善结果预测模型.
- 需要进行进一步的验证研究,但无监督的集群显示出增强诊断和理解病理生理学的前景.
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