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使用fNIRS进行中风后运动功能障碍的预测性名图.

Menghui Liu1, Chunxiao Wan2, Chunyan Wang2

  • 1Department of Neurological Rehabilitation, Shengli Oilfield Central Hospital, Dongying, Shandong, China.

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概括

这项研究开发了一种使用功能近红外光谱学 (fNIRS) 的诊断名录,以评估缺血性中风患者 (ULMD-IS) 上肢运动功能障碍. 血红素图标识出关键的血红蛋白水平作为风险因素,为客观评估提供了一个补充工具.

关键词:
功能近红外光谱学近红外光谱学缺血性中风 中风一个名字名字模型名字模型预测模型是一个预测模型.上肢运动功能障碍 上肢运动功能障碍

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科学领域:

  • 神经科学是一个神经科学.
  • 医疗成像医学成像
  • 生物医学工程 生物医学工程

背景情况:

  • 在缺血性中风患者上肢运动功能障碍 (ULMD-IS) 中缺乏客观评估工具.
  • 功能近红外光谱 (fNIRS) 为评估大脑活动提供了一种潜在的非侵入性方法.
  • 开发可靠的诊断工具对于有效的中风康复至关重要.

研究的目的:

  • 开发和验证用于评估ULMD-IS.的严重程度的诊断名录.
  • 利用fNIRS数据来确定ULMD-IS的客观生物标志物.
  • 提供一种补充工具,用于对中风后运动缺陷的临床评估.

主要方法:

  • 对275名ULMD-IS患者的回顾性分析.
  • 使用HOMER2软件进行数据预处理.
  • 在fNIRS数据上使用LASSO和多变量逻辑回归构建诊断名录.
  • 使用AUC,Hosmer-Lemeshow测试,校准曲线和DCA进行验证.

主要成果:

  • 确定了三个独立的风险因素:受影响部区域的脱氧血红蛋白 (HbD) 和总血红蛋白 (HbT) 在总和未受影响的前极区域.
  • 命名图表表现出良好的分化能力 (AUC:在训练中为0.766,在验证中为0.861).
  • 在已识别的风险因素和日常生活活动 (ADL) 评分之间没有发现显著的相关性.

结论:

  • 一种使用fNIRS衍生的血红蛋白水平的诊断型血红图成功地被开发用于ULMD-IS严重程度.
  • 诺莫格拉姆作为一个补充参考,用于客观评估运动功能障碍.
  • 该模型在预测治疗结果中的实用性需要谨慎解释,因为敏感性有限.