患者感知疼痛与数值评分系统之间的关系:使用电子健康记录数据进行前性验证
Lisiane Pruinelli1, Minh Nguyen2, Nicholas Stalter3
1College of Nursing and College of Medicine, University of Florida, Gainesville, FL, US.
Studies in health technology and informatics
|July 25, 2024
概括
这项研究引入了一种新的方法,使用临床对齐疼痛评估 (CAPA) 措施重建数值评分系统 (NRS) 疼痛评分. 开发的模型准确地预测NRS得分,为临床环境中的疼痛评估提供了有价值的工具.
科学领域:
- 疼痛医学 医学 疼痛医学
- 医疗信息学 医疗信息学
- 临床评估 临床评估
背景情况:
- 数值评分系统 (NRS) 是一种常见的疼痛评估工具.
- 仅使用NRS来获取全面的疼痛数据存在局限性.
- 临床对齐的疼痛评估 (CAPA) 提供了与疼痛相关的详细信息.
研究的目的:
- 开发和验证一种使用CAPA测量重建NRS疼痛评分的方法.
- 评估将CAPA组件与NRS分数联系起来的预测模型的准确性.
- 通过利用现有的临床数据来提高疼痛评估.
主要方法:
- 观察性回顾性队列研究,具有前性验证.
- 利用来自主要卫生系统 (2011-2020) 的非识别成年患者数据.
- 采用顺序回归模型,使用CAPA组件来预测NRS分数.
主要成果:
- 在所有CAPA组件和NRS得分之间发现了显著的关系.
- 该模型表现出良好的预测准确性,在开发集中RMSE为1.938和Somers' D为0.803.
- 前性验证结果为RMSE值2.1和Somers' D值0.74,证实了模型的有效性.
结论:
- 开发的方法准确地从CAPA测量中重建NRS疼痛得分.
- 这种方法提供了一种可靠的方式来估计NRS得分,当直接测量是不可用的.
- 该模型显示NRS分数在0到7之间具有特别的准确性.
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