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Updated: Jul 4, 2025

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公共数据预测的多药副作用在现实数据中仍然有效吗?
Gaeun Kee1, Hee Jun Kang2, Imjin Ahn1
1Department of Information Medicine, Asan Medical Center, 88, Olympicro 43gil, Songpagu, 05505, Seoul, Republic of Korea.
Heliyon
|February 2, 2024
概括
这项研究验证了一种药物相互作用预测模型,发现结合 cefpodoxime 和氨酸可显著增加真实患者数据中的肺风险.
科学领域:
- 药物监督 药物监督 药物监督
- 计算机化药物发现.
- 临床信息学是一种临床信息学.
背景情况:
- 对预测药物相互作用 (DDI) 的兴趣日益增长.
- 需要对预测的多药副作用的现实数据验证.
- 当前的预测往往缺乏经验验证.
研究的目的:
- 确认预测的多药性副作用是否与实际患者数据一致.
- 验证深度学习模型用于预测药物相互作用.
- 为了评估因 cefpodoxime-chlorpheniramine 同时使用而导致肺的真实风险.
主要方法:
- 利用基于深度学习的多药副作用预测模型.
- 从2000年1月到2020年12月对患者 (≥18岁) 的回顾性分析.
- 使用治疗权重的逆概率 (IPTW) 进行群组平衡,并使用卡普兰-梅尔和考克斯的比例危险模型分析结果.
主要成果:
- 确定了 cefpodoxime-chlorpheniramine-lung edema作为一个高风险的组合.
- 同时使用塞福多西姆和黄胺显著增加了1年的累积肺发病率 (p=0.001).
- 与单一治疗相比,观察到肺风险增加 (塞福多西姆的HR为2.10; 氨酸的HR为1.64).
结论:
- 多药学预测的现实数据验证有助于临床决策.
- 同时使用塞福多西姆和氨酸与长期肺风险增加有关.
- 这些发现支持加强对这种药物组合患者的监测.
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