Department of Pharmacokinetics & Pharmacodynamics, Gause Institute of New Antibiotics, Russian Academy of Medical Sciences, 11 Bolshaya Pirogovskaya Street, Moscow 119021, Russia; Department of Pharmaceutical and Toxicological Chemistry, I.M. Sechenov First Moscow State Medical University, Moscow, Russia.
Department of Pharmacokinetics & Pharmacodynamics, Gause Institute of New Antibiotics, Russian Academy of Medical Sciences, 11 Bolshaya Pirogovskaya Street, Moscow 119021, Russia.
Int J Antimicrob Agents. 2014 Oct;44(4):301-5. doi: 10.1016/j.ijantimicag.2014.06.013. Epub 2014 Jul 27.
The time inside the mutant selection window (TMSW) has been shown to be less predictive of selection of fluoroquinolone-resistant bacteria than the ratio of the area under the concentration-time curve to minimum inhibitory concentration (AUC/MIC). To explore the different predictive powers of TMSW and AUC/MIC, enrichment of ciprofloxacin-resistant mutants of four Escherichia coli strains was studied in an in vitro dynamic model at widely ranging TMSW values. Each organism was exposed to twice-daily ciprofloxacin for 3 days. Peak antibiotic concentrations were simulated to be close to the MIC, between the MIC and the mutant prevention concentration (MPC), and above the MPC, with TMSW varying from 0% to 100% of the dosing interval. Amplification of resistant mutants was monitored by plating on medium with 8× MIC of the antibiotic. For each organism, TMSW plots of the area under the bacterial mutant concentration-time curve (AUBCM) exhibited a hysteresis loop: at a given TMSW that corresponds to the points on the ascending portion of the bell-shaped AUBCM-AUC/MIC curve [when the time above the MPC (T>MPC) was zero], the AUBCM was greater than at the same TMSW related to the descending portion (T>MPC>0). A sigmoid function fits these separate data sets well for combined data with the four organisms (r(2)=0.81 and 0.92, respectively), in contrast to fitting the whole data pool while ignoring the AUC/MIC-resistance relationship (r(2)=0.61). These data allow the appropriate use of TMSW as a predictor of bacterial resistance.
突变选择窗(TMSW)内的时间预测氟喹诺酮耐药菌的选择能力不如浓度时间曲线下面积与最低抑菌浓度(AUC/MIC)的比值。为了探讨 TMSW 和 AUC/MIC 的不同预测能力,我们在体外动态模型中研究了四种大肠杆菌菌株的环丙沙星耐药突变体的富集情况,TMSW 值范围很广。每种生物体都接受了为期 3 天的每日两次环丙沙星暴露。模拟的峰值抗生素浓度接近 MIC、MIC 与突变预防浓度(MPC)之间以及 MPC 以上,TMSW 从给药间隔的 0%到 100%变化。通过在含有抗生素 8×MIC 的培养基上进行平板培养来监测耐药突变体的扩增。对于每种生物体,细菌突变浓度时间曲线下的 TMSW (AUBCM)图显示出滞后环:在与 AUBCM-AUC/MIC 曲线上升部分相对应的特定 TMSW (当 MPC 以上的时间(T>MPC)为零时),AUBCM 大于与下降部分相对应的相同 TMSW(T>MPC>0)。与忽略 AUC/MIC 耐药关系而拟合整个数据池(r(2)=0.61)相比,对于四个生物体的组合数据,该函数很好地拟合了这些单独的数据组(r(2)=0.81 和 0.92)。这些数据允许将 TMSW 作为细菌耐药性的预测指标进行适当使用。