开发临床风险预测模型,用于恶化心力衰竭事件和死因左心室喷射小部分的死亡
Rishi V Parikh1,2, Alan S Go1,3,4,5, Ankeet S Bhatt1,6
1Division of Research Kaiser Permanente Northern California Oakland CA USA.
Journal of the American Heart Association
|September 30, 2023
概括
研究人员开发了电子健康记录模型,以预测心力衰竭 (WHF) 事件和死亡的恶化. 这些模型在左心室喷射率 (LVEF) 类别中表现相似,有助于心力衰竭患者的风险分层.
科学领域:
- 心脏病学 心脏病学
- 医疗信息学 医疗信息学
- 预测分析是一种预测分析.
背景情况:
- 心力衰竭 (HF) 管理需要准确预测恶化的事件 (WHF) 和死亡率.
- 现有的预测模型往往在不同的临床环境和左心室喷射率 (LVEF) 类别中缺乏通用性.
- 需要强大的预测工具,利用全面的电子健康记录 (EHR) 数据.
研究的目的:
- 开发和验证基于EHR的预测模型,用于1年的WHF事件和全因死亡率.
- 为了评估LVEF的整个频谱的模型性能:具有减少EF的HF (HFrEF),具有轻度减少EF的HF (HFmrEF) 和具有保存EF的HF (HFpEF).
- 在综合医疗保健系统中确定WHF事件和死亡的关键预测因素.
主要方法:
- 在2011-2019年期间,对338,426名患有HF的成年人进行了回顾性队列研究.
- 使用自然语言处理和结构化EHR数据识别的WHF遭遇.
- 增强决策树组合模型开发用于预测1年的WHF事件和死亡,按LVEF分层 (<40%,40%-49%,≥50%).
主要成果:
- 这项研究包括18.0%的HFrEF,14.7%的HFmrEF和67.3%的HFpEF患者.
- 对于WHF事件和死亡的1年风险因LVEF类别而异.
- WHF预测模型的AUC值为0.76 (MSE 0.13),死亡模型的AUC值为0.83 (MSE 0.076).
- 除死亡外,模型性能和关键预测因素在WHF遭遇类型和LVEF类别中一致.
结论:
- 来自EHR的预测模型可以有效地预测1年的WHF事件和整个LVEF频谱的死亡率.
- 这些模型展示了强大的性能和通用性,为临床风险分层提供了有价值的工具.
- 在LVEF类别中没有观察到模型性能或预测指标的实质差异,突出显示了对HF风险预测的统一方法.
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