Mechanism-based pharmacodynamic models of fluoroquinolone resistance in Staphylococcus aureus

被引:27
作者
Chung, Philip
McNamara, Patrick J.
Campion, Jeffrey J.
Evans, Martin E.
机构
[1] Vet Affairs Med Ctr, Dept Internal Med, Div Infect Dis, Lexington, KY 40502 USA
[2] Univ Kentucky, Coll Pharm, Dept Pharmaceut Sci, Lexington, KY 40506 USA
[3] Univ Kentucky, Coll Med, Div Infect Dis, Dept Internal Med, Lexington, KY 40506 USA
关键词
D O I
10.1128/AAC.00736-05
中图分类号
Q93 [微生物学];
学科分类号
071005 ; 100705 ;
摘要
Pharmacodynamic modeling from earlier experiments in which two ciprofloxacin-susceptible Staphylococcus aureus strains and their corresponding resistant grlA mutants were exposed to a series of ciprofloxacin (J. J. Campion, P. J. McNamara, and M. E. Evans, Antimicrob. Agents Chemother. 49:209-219, 2005) and levo-floxacin (J. J. Campion et al., Antimicrob. Agents Chemother. 49:2189-2199, 2005) pharmacokinetic profiles in an in vitro system indicated that the subpopulation-specific estimated maximal killing rate constants were similar for both agents, suggesting a common mechanism of action. We propose two novel pharmacodynamic models that assign mechanisms of action to fluoroquinolones (growth inhibition or death stimulation) and compare the abilities of these models and two other maximum effect models (net effect and MIC based) to describe and predict the changes in the population dynamics observed during our previous in vitro system experiments with ciproffoxacin. A high correlation between predicted and observed viable counts was observed for all models, but the best fits, as assessed by diagnostic tests, and the most precise parameter estimates were obtained with the growth inhibition and net effect models. All models, except the death stimulation model, correctly predicted that resistant subpopulations would not emerge when a high-density culture was exposed to a high initial concentration designed to rapidly eradicate low-level-resistant grlA mutants. Additional experiments are necessary to elucidate which of the proposed mechanistic models best characterizes the antibacterial effects of fluoroquinolone antimicrobial agents.
引用
收藏
页码:2957 / 2965
页数:9
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