开发和验证可计算的表型,用于识别阿尔茨海默病患者,使用电子健康记录数据
medRxiv : the preprint server for health sciences
|February 19, 2024
概括
在电子健康记录 (EHR) 中准确识别阿尔茨海默病 (AD) 患者是一项挑战. 这项研究使用EHR数据开发了一个可计算的表型 (CP),改善了AD患者的分类.
科学领域:
- 生物医学信息学 生物医学信息学
- 临床数据科学 临床数据科学
- 神经科学研究 神经科学研究
背景情况:
- 阿尔茨海默病 (AD) 的错误分类在电子健康记录 (EHR) 中很常见,仅使用诊断代码.
- 准确的患者鉴定对于现实世界的证据研究至关重要.
研究的目的:
- 开发和验证可计算的表型 (CP) 用于识别阿尔茨海默病 (AD) 患者.
- 通过整合结构化和非结构化EHR数据来提高AD患者分类的准确性.
主要方法:
- 基于规则的可计算表型 (CP) 通过对电子健康记录数据的手动图表审查来代地开发.
- 使用来自多个医疗保健系统 (UF健康,UT健康,UMN) 的EHR数据验证了CP.
主要成果:
- 表现最好的CP结合了至少两个AD诊断与AD相关的关键词.
- 这个CP获得了高的F1分数:0.817 (UF健康),0.961 (UT健康) 和0.623 (UMN).
结论:
- 基于规则的CP在EHR中显示了AD识别的良好表现.
- 经过验证的CP对于在AD研究中利用现实世界EHR数据至关重要.
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