Quantitative assessment of combination antimicrobial therapy against multidrug-resistant bacteria in a murine pneumonia model.
Quantitative assessment of combination antimicrobial therapy against multidrug-resistant bacteria in a murine pneumonia model.
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在小鼠肺炎模型中针对多重耐药细菌的联合抗菌治疗的定量评估。
DOI：
10.1086/651024
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发表时间：
2010
期刊：
影响因子：
--
通讯作者：
Tam,VincentH
中科院分区：
文献类型：
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作者：
Yuan,Zhe;Ledesma,KimberlyR;Singh,Renu;Hou,Jingguo;Prince,RandallA;Tam,VincentH
背景：联合抗菌治疗是临床上控制多重耐药细菌感染的最后手段。然而，抗生素的选择往往是经验性的，联合药物作用的传统评估与临床结果无关。在这里，我们报告了一个定量的方法来评估联合杀灭抗微生物药物对2多药耐药bacteries.Methods.Combined时间-杀灭研究进行了临床可达到的浓度为每个2-剂组合对临床分离株ofAcinetobacter baumanniandPseudomonasaeruginosa。使用三维响应面对24 h时观察到的细菌负荷进行数学建模。随后，模拟临床剂量暴露的一个血小板减少性小鼠肺炎模型被用来验证我们的定量评估联合killing.Results.Different抗菌药物的组合被发现有不同的疗效对multidrugresistant细菌。正如我们的定量方法预测，头孢吡肟加阿米卡星被认为是最上级的组合，这是证明了减少组织细菌负荷和延长生存期的感染animals.Conclusions的数学模型和体内观察的预测之间的一致性证实了我们的定量方法的鲁棒性。这些数据强调了一种新的和有前途的方法，以指导合理选择抗菌药物组合在临床环境中。
Background.Combination antimicrobial therapy is clinically used as a last-resort strategy to control multidrugresistant bacterial infections. However, selection of antibiotics is often empirical, and conventional assessment of combined drug effect has not been correlated to clinical outcomes. Here, we report a quantitative method to assess combined killing of antimicrobial agents against 2 multidrug-resistant bacteria.Methods.Combined time-kill studies were performed using clinically achievable concentrations for each 2-agent combination against clinical isolates ofAcinetobacter baumanniiandPseudomonas aeruginosa. Bacterial burden observed at 24 h was mathematically modeled using a 3-dimensional response surface. Subsequently, a neutropenic murine pneumonia model with simulated clinical dosing exposures was used to validate our quantitative assessment of combined killing.Results.Different antimicrobial combinations were found to have varying efficacy against the multidrugresistant bacteria. As predicted by our quantitative method, cefepime plus amikacin was found to be the most superior combination, which was evidenced by a reduction in tissue bacterial burden and prolonged survival of infected animals.Conclusions.The consistency between the predictions of the mathematical model and in vivo observations substantiated the robustness of our quantitative method. These data highlighted a novel and promising method to guide rational selection of antimicrobial combination in the clinical setting.