量化疼痛位置和强度与多模式疼痛体图
Jereen Kwong1, Joanna Lin2, Ryan Leriche2
1Anesthesiology (Division of Pain Management), University of California, San Francisco.
Journal of visualized experiments : JoVE
|July 24, 2023
概括
这项研究引入了一种使用数字疼痛体图 (PBD) 来量化疼痛严重性的新方法. 这些PBD将绘图压力转化为颜色,提供与传统尺度相关的客观疼痛指标.
科学领域:
- 疼痛研究 疼痛研究
- 医学技术 医学技术 医学技术
- 量化心理学 量化心理学
背景情况:
- 标准化疼痛尺度 (NRS,VAS,MPQ) 是主观的,可能无法捕捉疼痛的复杂性.
- 临床实践使用定性疼痛体图 (PBD) 来绘制疼痛位置.
- 现有的方法缺乏客观,可量化的疼痛评估工具.
研究的目的:
- 开发和验证一种从PBD中提取可量化的指标的方法.
- 评估新型PBD指标与已建立的疼痛尺度之间的相关性.
- 引入一种更全面的疼痛表征方法.
主要方法:
- 利用一个数字平板电脑和带有压力色调转换的笔笔来创建PBD.
- 定义了新的可量化的指标:PBD平均强度,覆盖范围和总强度.
- 使用相关性和信息理论与数值评分表 (NRS),视觉模拟表 (VAS) 和麦吉尔疼痛问卷 (MPQ) 进行验证的PBD指标.
主要成果:
- 新型PBD指标与NRS,VAS和MPQ具有很高的一致性.
- 压力-色调转换有效地将绘图压力转化为可量化的色彩数据.
- PBD提供客观,空间和定量疼痛信息.
结论:
- 可量化的PBD为疼痛评估提供了一种新的客观方法.
- 这种技术为全面的疼痛特征提供空间和定量数据.
- 对于疼痛监测,PBD指标可以反复测量和随着时间的推移跟踪.
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