引用本文: | 叶红波,芮建中,薛领.NONMEM法优化替考拉宁专家共识中肾功能不全时的治疗方案[J].中国现代应用药学,2019,36(15):1959-1962. |
| YE Hongbo,RUI Jianzhong,XUE Ling.Teicoplanin Dosage Regimens Optimization for Renal Insufficiency by NONMEN Method According to Expert Consensus[J].Chin J Mod Appl Pharm(中国现代应用药学),2019,36(15):1959-1962. |
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摘要: |
目的 探讨不同肾功能状态下替考拉宁治疗耐甲氧西林金黄色葡萄球菌感染的合理剂量,优化专家共识的给药方案。方法 采用非线性混合效应模型NONMEM工具进行蒙特卡洛模拟,以药时曲线下面积AUC0-24/最低抑菌浓度≥345和首剂维持剂量时谷浓度>30 mg·L-1作为达标条件,模拟3种体质量、5种肌酐清除率下的替考拉宁的达标概率和累计反应百分率。结果 发现专家共识中推荐的6~12 mg·kg-1在不同肾功能状态下的负荷剂量从9.2 mg·kg-1增至11.1 mg·kg-1,差别最大1.9 mg·kg-1。结论 蒙特卡洛模拟结果提示替考拉宁的专家共识推荐的给药方案需要进一步明确。 |
关键词: 替考拉宁 蒙特卡洛模拟 谷浓度 专家共识 |
DOI:10.13748/j.cnki.issn1007-7693.2019.15.020 |
分类号:R969.3 |
基金项目: |
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Teicoplanin Dosage Regimens Optimization for Renal Insufficiency by NONMEN Method According to Expert Consensus |
YE Hongbo1, RUI Jianzhong2, XUE Ling3
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1.Department of Pharmacy, Anji Traditional Chinese Medicine Hospital, Huzhou 313100, China;2.Department of Pharmacology, Nanjing General Hospital of PLA, Nanjing 210002, China;3.Department of Clinical Pharmacology, the First Affiliated Hospital of Soochow University, Suzhou 215006, China
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Abstract: |
OBJECTIVE To explore the reasonable dose of teicoplanin for methicillin-resistant Staphylococcus aureus infection under different renal function status, and to optimize the expert consensus drug dosage plan. METHODS Two indices which were AUC0-24/MIC ≥ 345 and trough concentration >30 mg·L-1 were applied for the Monte Carlo simulations with NONMEM. The probability of target attainment and cumulative fraction of response were calculated among patients with three types of body weight and five types of renal dysfunction. RESULTS The result showed that the recommended loading dose of 6-12 mg·kg-1 recommended by experts in different renal function states increased from 9.2 to 11.1 mg·kg-1, with a maximum difference of 1.9 mg·kg-1. CONCLUSION The Monte Carlo simulation results suggest that the dosing regimen recommended by the expert consensus of teicoplanin needs to be further clarified. |
Key words: teicoplanin Monte Carlo simulation trough concentration expert consensus |