基于电子健康记录 (EHR) 的风险计算器可以预测骨折与FRAX相比:一个概念验证研究
Rajesh K Jain1, Eric Polley2, Mark Weiner3
1Section of Endocrinology, Diabetes, and Metabolism, Department of Medicine, The University of Chicago, 5841 S Maryland Ave, MC 1027, Chicago, IL, 60637, USA. rjain2@bsd.uchicago.edu.
概括
电子健康记录 (EHR) 可以使用常规数据预测骨折风险,消除了手动风险因素评估的需要. 这项研究开发并验证了一种基于EHR的骨折风险模型,与现有工具可比.
科学领域:
- 骨质疏松症和骨折风险评估 骨质疏松症和骨折风险评估
- 临床信息学和电子健康记录
- 在医疗保健中的预测建模.
背景情况:
- 像FRAX这样的传统骨折风险计算器在临床工作流程之外运行.
- 电子健康记录 (EHR) 是临床工作流程的核心,并包含潜在的骨折预测因素.
- 在EHR中需要集成的骨折风险预测工具.
研究的目的:
- 评估EHR变量对预测骨折的有用性.
- 开发和内部验证基于EHR的骨折风险模型作为概念验证.
- 评估EHR数据是否可以取代手动确定骨折风险因素.
主要方法:
- 利用了来自24,189名初级保健患者 (2010-2018) 的常规临床数据.
- 使用医生诊断码识别主要骨质疏松性骨折 (MOFs).
- 在一个训练集上开发了一个使用考克斯回归和向后逐步选择的预测模型,然后在一个测试集上验证,将性能与FRAX进行比较.
主要成果:
- 来自EHR的变量包括生命体征,诊断,药物和实验室值与事件MOF相关.
- 最终的模型包括19个变量,包括年龄,BMI,帕金森病,慢性病和白蛋白.
- 基于EHR的模型在测试组中显示了可比的歧视 (AUC为0.73比0.70) 和对FRAX的校准.
结论:
- 常规收集的EHR数据可以在没有手动数据收集的情况下充分预测骨折风险.
- 可以开发和验证基于EHR的骨折风险模型.
- 在护理点进行自动骨折预测是可行的,这可能会改善骨质疏松症的查和治疗.
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