在老年门诊患者中开发和验证一种基于药物的急性损伤风险预测模型
Mee Yeon Lee1, Kyu-Nam Heo1, Suhyun Lee1
1College of Pharmacy and Research Institute of Pharmaceutical Sciences, Seoul National University, 1, Gwanak-ro, Gwanak-gu, Seoul 08826, Republic of Korea.
Archives of gerontology and geriatrics
|February 21, 2024
概括
一个新的模型使用药物数据预测了老年人急性损伤 (AKI) 风险. 它识别高风险患者进行有针对性的干预,改善社区环境中的预防.
科学领域:
- 腎臟病學 (nephrology) 是一種醫學專業.
- 老年病的医生 老年病的医生
- 药理学 药理学是指药理学的学科.
背景情况:
- 老年人面临急性损伤 (AKI) 的高风险,特别是在门诊机构,经常与药物使用有关.
- 现有的AKI预测模型在这个人群中是有限的,特别是那些整合药物特定因素的预测模型.
- 迫切需要工具来识别高风险的老年门诊患者,以积极预防AKI.
研究的目的:
- 开发和验证一种新的急性损伤 (AKI) 风险预测模型.
- 将与药物相关的变量纳入老年门诊患者的AKI风险模型.
- 加强在社区护理中识别 AKI 风险较高的个人.
主要方法:
- 分析了一大群超过220万名65岁及以上的门诊患者.
- 使用70%的训练集开发了一个后勤回归模型,并在30%的训练集上验证.
- 该模型选了170个变量,重点关注人口统计,并发病和与药物相关的因素,以预测一个月内新发的AKI.
主要成果:
- 最终的预测模型包括12个变量:2个是人口统计,2个是并发症,4个是药物相关的,6个是药物相关的.
- 该模型在验证队列中表现出良好的性能,AUC为0.720.
- 根据模型确定的高风险患者与低风险患者相比,AKI的风险增加了27倍.
结论:
- 为老年门诊患者开发了一种新的,经过验证的AKI风险预测模型.
- 该模型有效地纳入了与药物相关的变量,为AKI风险提供了良好的歧视.
- 这种工具可以帮助识别和准老年门诊患者进行干预,以预防急性损伤.
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