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针选择和组合在三角神经疼痛针治疗中的分析:数据挖掘的协议

Yujun He¹, Lu Li¹, Miao Zhou¹

¹Department of Traditional Chinese Medicine, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Taizhou City, People's Republic of China.

Journal of pain research

|July 8, 2025

概括

这项研究使用数据挖掘来找到三角神经疼痛 (TN) 的最佳针点. 这些发现将指导这种神经病痛疾病的标准化治疗.

科学领域:

神经学神经学
疼痛管理疼痛管理
综合医学是一个整体的医学.

背景情况:

三神经疼痛 (TN) 是一种神经病痛疾病,严重影响生活质量.
针对TN有希望,但最佳针点选择缺乏共识.
多样化的治疗方法阻碍了对止痛机制的标准化和理解.

研究的目的:

执行第一个全面的数据挖掘分析的临床试验针TN.
为了确定TN治疗中最有效的针点选择和组合.

主要方法:

在2025年5月之前,对8个主要数据库进行系统搜索.
包括评估TN针的临床试验.
使用描述性统计,关联规则分析,因子分析,集群分析和决策树分析来提取和分析数据.

主要成果:

确定三角神经疼痛中最有效的针点选择和组合.
基于数据的洞察力,为TN提供最佳的针点应用.

结论:

这项研究将为TN治疗中针点选择提供基于证据的建议.
这些发现旨在支持临床医生和患者做出明智的治疗决策.
这项研究有助于对神经性面部疼痛的针方案进行标准化.

关键词:

针是一种针,针是一种针.协会规则分析协会规则分析集群分析集群分析集群分析数据挖掘是数据挖掘的一个方法.决策树的分析描述性统计数据描述性的统计数据探索性的因素分析.三胞胎神经疼痛三胞胎神经疼痛

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