使用决策树模型来准15-30μg/mL的血清最低度的24小时充值剂量方案:一个回顾性研究
Shoji Kondo1, Kazutaka Oda2, Tetsuya Kaneko3
1Department of Pharmacy, Kumamoto University Hospital, 1-1-1, Honjo, Chuo-ku, Kumamoto, Japan; Department of Infection Control, Kumamoto University Hospital, 1-1-1, Honjo, Chuo-ku, Kumamoto, Japan; Department of Clinical Pharmaceutical Sciences, Graduate School of Pharmaceutical Sciences Kumamoto University, 5-1, Oe, Chuo-ku, Kumamoto, Japan.
概括
这项研究开发了一种24小时的泰可普拉宁 (TEIC) 加载剂量方案,以快速达到严重感染的治疗度. 一个决策树模型确定了影响最佳TEIC剂量的关键患者因素.
科学领域:
- 药理学 药理学是指药理学的学科.
- 传染性疾病 传染性疾病
- 临床药房 临床药房
背景情况:
- 泰科普拉宁 (TEIC) 通常在36-48小时内用于严重感染.
- 快速达到治疗性TEIC度 (15-30μg/mL) 对于治疗毒症和MRSA感染等严重疾病至关重要.
研究的目的:
- 为了建立一个在24小时内完成的teicoplanin加载剂量方案.
- 通过使用决策树 (DT) 模型,识别影响最佳负载剂量的患者特定因素.
主要方法:
- 在2017年1月至2022年12月期间接受TEIC的149名患者的回顾性分析.
- 开发和验证DT模型,以确定正确的TEIC负载剂量 (LD22.5),目标为22.5μg/mL.
- 使用R2值与人口药理动力学 (PopPK) 模型相比,评估DT模型的有效性.
主要成果:
- 平均LD22.5的14.5毫克/公斤是指定的.
- 确定了影响TEIC加载剂量的四个关键因素:估计的淋巴细胞过率,年龄,白蛋白和C反应蛋白.
- DT模型实现了0.724 (训练) 和0.695 (测试) 的R2值,与PopPK模型相比.
结论:
- 成功建立了24小时的提克洛普拉宁充值剂量方案.
- 该研究确定了影响TEIC剂量的关键因素,从而实现了个性化治疗策略.
- 开发的DT算法为优化teicoplanin加载剂量提供了一个实用的工具.
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