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在出院处方中探索潜在的药物相互作用:ChatGPT在评估这些相互作用方面的有效性
Rahi Bikram Thapa1, Subash Karki1, Sabin Shrestha2
1Department of Pharmacy, Purbanchal University School of Health Science, Gothgaun, Morang, Nepal.
Exploratory research in clinical and social pharmacy
|February 3, 2025
概括
潜在的药物相互作用 (pDDI) 在医院出院处方中很常见. 虽然像ChatGPT-4.0这样的AI可以识别pDDI发生,但人类监督对于严重程度和发病预测的准确性至关重要.
科学领域:
- 临床药房 临床药房
- 医疗保健中的人工智能
- 药物监督 药物监督 药物监督
背景情况:
- 潜在的药物相互作用 (pDDI) 具有显著的临床风险,增加了发病率,死亡率和医疗保健费用.
- 像Micromedex这样的既定工具有助于pDDI查,但新兴的人工智能,如ChatGPT,为补充预测提供了潜力.
- 在pDDI检测中AI的临床可靠性和准确性仍然在很大程度上未经验证.
研究的目的:
- 为了在内部医学出院处方中评估pDDI.
- 为了比较ChatGPT-4.0在预测pDDI中的疗效与Micromedex药物相互作用检查器.
主要方法:
- 一项涉及301名出院患者的横截面研究,持续了三个月.
- 使用Micromedex识别的pDDI,详细说明发生,严重程度,发病和文档.
- 与Micromedex数据对比,分析了ChatGPT-4.0的预测;二进制后勤回归评估了pDDI风险因素.
主要成果:
- 总共有1551种药物被处方给301名患者 (平均每名患者5.15).
- 在60.13%的患者中发现了pDDI (平均每患者3.17).
- 聊天GPT-4.0实现了对pDDI发生的100%准确性,但对严重程度 (37.3%) 和发病 (65.2%) 的准确性较低. 多种药物显著增加了pDDI风险 (OR: 3.960,p < 0.001).
结论:
- 在内部医学解药处方中,pDDI非常普遍,多药作为一个重要的风险因素.
- 聊天GPT-4.0在识别pDDI发生时表现出高准确度.
- 在ChatGPT-4.0预测严重程度和发病的局限性需要持续的临床警和专业监督.
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