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An Improved Method for Collection of Cerebrospinal Fluid from Anesthetized Mice06:40

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This protocol describes an improved technique for the abundant collection of cerebrospinal fluid (CSF) with no contamination from blood. With greater sample collection and purity, more analyses can be performed using CSF to further our understanding of diseases that affect the brain and spinal...
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A reference measurement procedure for the absolute quantification of Aβ1-42 in human CSF based on solid-phase extraction and liquid chromatography tandem mass spectrometry is...
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We present a biochemical and behavioral protocol to evaluate the efficacy of mitochondria-targeted water-soluble compounds for the treatment of Spinocerebellar ataxia type 1 (SCA1) and other cerebellar neurodegenerative diseases.
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相关实验视频

Updated: Jan 9, 2026

An Improved Method for Collection of Cerebrospinal Fluid from Anesthetized Mice
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使用数据逻辑分析方法来评估运动心电图后的长期死亡风险.

Michael S Lauer1, Sorin Alexe, Claire E Pothier Snader

  • 1Department of Cardiology of the Cleveland Clinic Foundation, Cleveland, Ohio 44195, USA. Lauerm@ccf.org

Circulation
|August 7, 2002
PubMed
概括
此摘要是机器生成的。

数据的逻辑分析确定了高风险患者子组,死亡风险增加. 这种数学优化方法在风险分层方面被证明是有效的,与回归技术相当.

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科学领域:

  • 生物统计学 生物统计学
  • 医疗信息学 医疗信息学
  • 数学优化的数学优化

背景情况:

  • 数据逻辑分析 (LAD) 是一种数学优化技术.
  • LAD系统地识别模式,称为"综合征".
  • 这项研究探讨了患者风险分层的LAD,并将其与回归方法进行比较.

研究的目的:

  • 应用数据的逻辑分析,以在大量患者队列中进行风险分层.
  • 将LAD的疗效与传统的回归技术进行比较,以预测患者的结果.
  • 确定与显著增加或减少死亡风险相关的特定患者亚组 (综合征).

主要方法:

  • 应用LAD对9454名接受运动测试的患者队列,使用20个变量.
  • 定义的高风险综合征 (与死亡风险增加>5倍相关) 和低风险综合征 (与死亡风险降低>5倍相关).
  • 根据培训和验证套件中识别的综合征,推导和验证的风险得分.

主要成果:

  • 确定了15种高风险综合征和26种低风险综合征.
  • 来自LAD的风险评分预测了5年死亡率,确定了21%的验证队列具有高风险 (11%对1%的死亡率).
  • 在死亡事件中,LAD风险得分占67%,显示出强大的预测能力 (HR 8.3).

结论:

  • 数据的逻辑分析有效地确定了患者子集,其死亡风险大幅增加.
  • 在风险分层方面,LAD方法表现出强的表现,与考克斯回归可比.
  • 需要进一步的研究来优化LAD在风险分层方面的临床应用.