Literature DB >> 26643328

Searching for the Optimal Predictor of Ciprofloxacin Resistance in Klebsiella pneumoniae by Using In Vitro Dynamic Models.

Elena N Strukova1, Yury A Portnoy1, Andrey V Romanov2, Mikhail V Edelstein2, Stephen H Zinner3, Alexander A Firsov4.   

Abstract

There is growing evidence of applicability of the hypothesis of the mutant selection window (MSW), i.e., the range between the MIC and the mutant prevention concentration (MPC), within which the enrichment of resistant mutants is most probable. However, it is not clear if MPC-based pharmacokinetic variables are preferable to the respective MIC-based variables as interstrain predictors of resistance. To examine the predictive power of the ratios of the area under the curve (AUC24) to the MPC and to the MIC, the selection of ciprofloxacin-resistant mutants of three Klebsiella pneumoniae strains with different MPC/MIC ratios was studied. Each organism was exposed to twice-daily ciprofloxacin for 3 days at AUC24/MIC ratios that provide peak antibiotic concentrations close to the MIC, between the MIC and the MPC, and above the MPC. Resistant K. pneumoniae mutants were intensively enriched at an AUC24/MIC ratio of 60 to 360 h (AUC24/MPC ratio from 2.5 to 15 h) but not at the lower or higher AUC24/MIC and AUC24/MPC ratios, in accordance with the MSW hypothesis. AUC24/MPC and AUC24/MIC relationships with areas under the time courses of ciprofloxacin-resistant K. pneumoniae (AUBCM) were bell shaped. These relationships predict highly variable "antimutant" AUC24/MPC ratios (20 to 290 h) compared to AUC24/MIC ratios (1,310 to 2,610 h). These findings suggest that the potential of the AUC24/MPC ratio as an interstrain predictor of K. pneumoniae resistance is lower than that of the AUC24/MIC ratio.
Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Entities:  

Mesh:

Substances:

Year:  2015        PMID: 26643328      PMCID: PMC4775939          DOI: 10.1128/AAC.02334-15

Source DB:  PubMed          Journal:  Antimicrob Agents Chemother        ISSN: 0066-4804            Impact factor:   5.191


  31 in total

Review 1.  Antibiotics in the clinical pipeline in 2013.

Authors:  Mark S Butler; Mark A Blaskovich; Matthew A Cooper
Journal:  J Antibiot (Tokyo)       Date:  2013-09-04       Impact factor: 2.649

2.  Enrichment of resistant Staphylococcus aureus at ciprofloxacin concentrations simulated within the mutant selection window: bolus versus continuous infusion.

Authors:  Alexander A Firsov; Maria V Smirnova; Elena N Strukova; Sergey N Vostrov; Yury A Portnoy; Stephen H Zinner
Journal:  Int J Antimicrob Agents       Date:  2008-09-14       Impact factor: 5.283

3.  Mutant prevention concentration-based pharmacokinetic/pharmacodynamic indices as dosing targets for suppressing the enrichment of levofloxacin-resistant subpopulations of Staphylococcus aureus.

Authors:  Beibei Liang; Nan Bai; Yun Cai; Rui Wang; Karl Drlica; Xilin Zhao
Journal:  Antimicrob Agents Chemother       Date:  2011-02-22       Impact factor: 5.191

4.  Bacterial antibiotic resistance studies using in vitro dynamic models: Population analysis vs. susceptibility testing as endpoints of mutant enrichment.

Authors:  Alexander A Firsov; Elena N Strukova; Yury A Portnoy; Darya S Shlykova; Stephen H Zinner
Journal:  Int J Antimicrob Agents       Date:  2015-07-16       Impact factor: 5.283

Review 5.  Restricting the selection of antibiotic-resistant mutants: a general strategy derived from fluoroquinolone studies.

Authors:  X Zhao; K Drlica
Journal:  Clin Infect Dis       Date:  2001-09-15       Impact factor: 9.079

6.  Activities of moxifloxacin against, and emergence of resistance in, Streptococcus pneumoniae and Pseudomonas aeruginosa in an in vitro pharmacokinetic model.

Authors:  Alasdair P MacGowan; Chris A Rogers; H Alan Holt; Karen E Bowker
Journal:  Antimicrob Agents Chemother       Date:  2003-03       Impact factor: 5.191

7.  ABT492 and levofloxacin: comparison of their pharmacodynamics and their abilities to prevent the selection of resistant Staphylococcus aureus in an in vitro dynamic model.

Authors:  Alexander A Firsov; Sergey N Vostrov; Irene Yu Lubenko; Alexander P Arzamastsev; Yury A Portnoy; Stephen H Zinner
Journal:  J Antimicrob Chemother       Date:  2004-06-09       Impact factor: 5.790

8.  Bacterial resistance studies using in vitro dynamic models: the predictive power of the mutant prevention and minimum inhibitory antibiotic concentrations.

Authors:  Alexander A Firsov; Elena N Strukova; Darya S Shlykova; Yury A Portnoy; Varvara K Kozyreva; Mikhail V Edelstein; Svetlana A Dovzhenko; Mikhail B Kobrin; Stephen H Zinner
Journal:  Antimicrob Agents Chemother       Date:  2013-07-29       Impact factor: 5.191

9.  Emergence of resistant Streptococcus pneumoniae in an in vitro dynamic model that simulates moxifloxacin concentrations inside and outside the mutant selection window: related changes in susceptibility, resistance frequency and bacterial killing.

Authors:  Stephen H Zinner; Irene Yu Lubenko; Deborah Gilbert; Kelly Simmons; Xilin Zhao; Karl Drlica; Alexander A Firsov
Journal:  J Antimicrob Chemother       Date:  2003-09-01       Impact factor: 5.790

10.  Mutations in gyrA and parC genes in nalidixic acid-resistant Escherichia coli strains from food products, humans and animals.

Authors:  Yolanda Sáenz; Myriam Zarazaga; Laura Briñas; Fernanda Ruiz-Larrea; Carmen Torres
Journal:  J Antimicrob Chemother       Date:  2003-03-13       Impact factor: 5.790

View more
  2 in total

Review 1.  What Antibiotic Exposures Are Required to Suppress the Emergence of Resistance for Gram-Negative Bacteria? A Systematic Review.

Authors:  Chandra Datta Sumi; Aaron J Heffernan; Jeffrey Lipman; Jason A Roberts; Fekade B Sime
Journal:  Clin Pharmacokinet       Date:  2019-11       Impact factor: 6.447

2.  Synergistic Combination of Linezolid and Fosfomycin Closing Each Other's Mutant Selection Window to Prevent Enterococcal Resistance.

Authors:  Lifang Jiang; Na Xie; Mingtao Chen; Yanyan Liu; Shuaishuai Wang; Jun Mao; Jiabin Li; Xiaohui Huang
Journal:  Front Microbiol       Date:  2021-02-09       Impact factor: 5.640

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.