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首页> 外文期刊>Antimicrobial agents and chemotherapy. >Pharmacodynamic model to describe the concentration-dependent selection of cefotaxime-resistant Escherichia coli.
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Pharmacodynamic model to describe the concentration-dependent selection of cefotaxime-resistant Escherichia coli.

机译:药效学模型来描述耐头孢噻肟大肠埃希菌的浓度依赖性选择。

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摘要

Antibiotic dosing regimens may vary in their capacity to select mutants. Our hypothesis was that selection of a more resistant bacterial subpopulation would increase with the time within a selective window (SW), i.e., when drug concentrations fall between the MICs of two strains. An in vitro kinetic model was used to study the selection of two Escherichia coli strains with different susceptibilities to cefotaxime. The bacterial mixtures were exposed to cefotaxime for 24 h and SWs of 1, 2, 4, 8, and 12 h. A mathematical model was developed that described the selection of preexisting and newborn mutants and the post-MIC effect (PME) as functions of pharmacokinetic parameters. Our main conclusions were as follows: (i) the selection between preexisting mutants increased with the time within the SW; (ii) the emergence and selection of newborn mutants increased with the time within the SW (with a short time, only 4% of the preexisting mutants were replaced by newborn mutants, compared to the longest times, where 100% were replaced); and (iii) PME increased with the area under the concentration-time curve (AUC) and was slightly more pronounced with a long elimination half-life (T(1/2)) than with a short T(1/2) situation, when AUC is fixed. We showed that, in a dynamic competition between strains with different levels of resistance, the appearance of newborn high-level resistant mutants from the parental strains and the PME can strongly affect the outcome of the selection and that pharmacodynamic models can be used to predict the outcome of resistance development.
机译:抗生素给药方案选择突变体的能力可能有所不同。我们的假设是,在选择性窗口(SW)内,即当药物浓度介于两个菌株的MIC之间时,选择更具抗药性的细菌亚群的时间会增加。体外动力学模型用于研究对头孢噻肟敏感性不同的两种大肠杆菌菌株的选择。将细菌混合物暴露于头孢噻肟24小时,SW分别为1、2、4、8和12小时。建立了数学模型,该模型描述了现有突变体和新生儿突变体的选择以及MIC后效应(PME)作为药代动力学参数的函数。我们的主要结论如下:(i)预先存在的突变体之间的选择随着SW内时间的增加而增加; (ii)新生突变体的出现和选择随西南部时间的增加而增加(在很短的时间内,只有4%的既存突变体被新生突变体替代,而最长的时间是100%被替换); (iii)PME随着浓度-时间曲线(AUC)下面积的增加而增加,消除半衰期长(T(1/2))的情况比T(1/2)短的情况略显明显,当固定AUC时。我们显示,在具有不同抗性水平的菌株之间的动态竞争中,来自亲本菌株和PME的新生儿高水平抗性突变体的出现会强烈影响选择的结果,并且药效学模型可用于预测抵抗力发展的结果。

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