As resistance to available antibiotics increases in the United States, surveillance studies are needed to track the emerging pathogens of concern. In the hospital setting, resistance among Gram-negative bacteria continues to be a challenge facing prescribers. In recent years, Pseudomonas aeruginosa resistance to carbapenems and fluoroquinolones has increased to approximately 15% to 25% in some reports.1-3 Acinetobacter species are frequently multidrug resistant and only the carbapenems commonly retain activity against this pathogen.1,4 Lastly, extended spectrum β-lactamases (ESBLs) have become prevalent among Klebsiella species and Escherichia coli. In addition to β-lactams, many ESBL-harboring pathogens are also resistant to fluoroquinolones and aminoglycosides.5
Although the surveillance of emerging resistance is important, the susceptibility of the drug against the bacteria does not always correlate well with clinical outcomes.6 Knowledge of an antibiotic's pharmacodynamic profile is needed to interpret what dose and dosing interval are needed to achieve optimal bactericidal exposure.7,8 The Optimizing Pharmacodynamic Target Attainment using a Microbiology Antibiogram (OPTAMA) program aims to determine the likelihood of specific antibiotic regimens achieving definitive pharmacodynamic exposures. Previous OPTAMA studies were conducted using 2002 isolates of E. coli, Klebsiella species, Acinetobacter baumannii, and P. aeruginosa collected from North America, South America, and Europe.9-11 These studies observed that the carbapenems (ie, imipenem and meropenem) retained high likelihood of achieving bactericidal exposure against these bacteria. In contrast, the ability of ciprofloxacin to achieve bactericidal exposure was the lowest in all regions of the world and was significantly lower than that predicted by percentage of susceptibility.
As is commonly done for microbiology surveillance studies, it is prudent to reevaluate the likelihood of these antibiotic regimens achieving bactericidal exposures against a current population of these bacteria and compare these results with previous data to examine the trends.
Pharmacodynamic exposures, as measured by percentage of time above the minimum inhibitory concentration (MIC) for free (ie, unbound) drug (fT>MIC), were modeled against all isolates for 30-minute intravenous (IV) infusion regimens of cefepime (dosage, 1 g every 12 hours), ceftazidime (dosage, 1 g every 8 hours), imipenem (dosage, 1 g every 8 hours), meropenem (dosage, 1 g every 8 hours), and piperacillin/tazobactam (dosage, 3.375 g every 6 hours). Against P. aeruginosa and A. baumannii, additional dosing regimens examined included cefepime (dosage, 2 g every 12 hours), ceftazidime (dosage, 2 g every 8 hours), and piperacillin-tazobactam (dosage, 3.375 g every 4 hours). A 1-compartment IV-infusion equation was used to calculate fT>MIC for the β-lactams. Pharmacodynamic exposures for ciprofloxacin (dosages, 400 mg every 12 hours and 400 mg every 8 hours) were measured by calculation of the total drug 24-hour area under the concentration curve (AUC) divided by the MIC (ie, AUC/MIC). Total drug AUC for ciprofloxacin were calculated by dividing the dose by the total clearance (CL T) value. The AUC/MIC was then calculated by dividing the total drug AUC for the ciprofloxacin regimen by the MIC. The total drug AUC/MIC ratio was used instead of that of the free drug because the original studies evaluating the pharmacodynamic breakpoint for ciprofloxacin did not account for free drug in those patients.12 The dosing regimens chosen reflected those that are FDA approved, used at Hartford Hospital, and/or commonly administered by our infectious disease colleagues throughout North America.
Microbiology data used during the pharmacodynamic analyses were derived from the Meropenem Yearly Susceptibility Test Information Collection (MYSTIC) database. The MYSTIC program contains a large set of data for nosocomial isolates from around the world and associated information on the MICs for these isolates. This global, multicenter surveillance study compares the activity of meropenem, along with that of imipenem, ertapenem, ceftazidime, cefepime, piperacillin/tazobactam, aztreonam, ceftriaxone, ciprofloxacin, and levofloxacin, in high-prescribing centers against Gram-positive and Gram-negative nosocomial isolates.4
The data aggregated in the present study were generated from isolates collected consecutively from patients hospitalized in North America during the 2004 edition of the MYSTIC program.13 North American participants in the 2004 MYSTIC program included 15 medical centers located in Arkansas, California, Colorado, Delaware, Iowa, Kentucky, Louisiana, Nebraska, New York, Tennessee, Texas, Ohio, Utah, and Washington, and 4 Canadian institutions. A total of 689 P. aeruginosa, 111 A. baumannii, 724 E. coli, and 430 Klebsiella species (ie, Klebsiella pneumoniae and oxytoca) were tested against the desired antibiotics. Five new institutions that did not contribute in 2002 provided isolates in 2004, and these isolates were eliminated from this analysis for consistency when comparing 2002 and 2004 data. Therefore, 639 P. aeruginosa, 103 A. baumannii, and 705 E. coli isolates, and 418 Klebsiella species were included. All resultant isolates were obtained from patients in the intensive care unit (ICU). Multiple isolates of the same species from a single origin (same patient) were excluded. Each participant laboratory performed identification at the species level by colony morphology or by simple biochemical tests (spot indole, bile solubility, oxidase, etc) or Vitek ID cards (BioMerieux, Hazelwood, Mo) when required.
The MICs of all antibiotics were determined at a central laboratory by either broth microdilution or agar dilution according to Clinical Laboratory Standards Institute (CLSI) methodology.14 The detailed methodology for MIC determination has been published in an article by Rhomberg and Jones.4 MICs ranged from 0.008 μg/mL or less to 256 μg/mL or more in doubling dilutions for all antibiotics. The MIC values less than or equal to 0.008 μg/mL or greater than or equal to 256 μg/mL were classified as 0.008 μg/mL or 256 μg/mL, respectively. The percentages of isolates at each MIC are listed in Table 1. Custom MIC distributions were built for each population of bacteria on the basis of the MIC frequencies in the MYSTIC program antibiogram using Crystal Ball 2000 (Decisioneering, Inc, Denver, Colo), whereby the percentage of bacteria at each MIC is treated as a frequency and the values between the MICs do not exist.
Pharmacokinetic parameters used to analyze these data are listed in Table 2.10 These data were obtained from previously published studies in healthy volunteers.15-23 This method has the advantage of comparing different antibiotics in a similar population. For studies to be considered, they must have described the assay used to determine drug concentrations, used clinically relevant dosing regimens, performed an adequate pharmacokinetic analysis as determined by OPTAMA investigators, and presented the means and SDs for CL T and the volume of distribution at steady state (V d). For studies reporting pharmacokinetic profiles as a 2-compartment model, the V dβ was calculated from the terminal elimination rate constant for use in the 1-compartment model.15,17 The CL T and V d values were assumed to follow log Gaussian distributions during simulations.
Estimates of the fraction unbound for all β-lactams were derived from the package insert for each antibiotic and among the other studies previously described. The unbound fractions for these agents were treated as ranges and are also listed in Table 2. It was assumed that the fraction unbound followed a uniform distribution, whereby any value within the simulated range had an equal probability of occurring.
Monte Carlo Simulation
A 5000-subject Monte Carlo simulation (Crystal Ball 2000) was conducted to calculate the estimates of fT>MIC or total AUC/MIC ratio for each antibiotic regimen/bacterial population combination. During each iteration, different values for CL T, V d, the unbound fraction of drug (f u), and MIC were substituted into the appropriate equations on the basis of the probability distributions for each, thereby resulting in 5000 different estimates of pharmacodynamic exposure for each antibiotic regimen against each bacterial population. Values for fT>MIC and total AUC/MIC ratio were plotted on frequency curves for further analysis. For comparative purposes, the cumulative fraction of response (CFR) was determined for all antibacterial dosing regimens against each bacterial population of interest. The CFR is a term similar to pharmacodynamic target attainment that expresses the probability of achieving an exposure with a given dosing regimen against a population of pathogens.24 The CFR for obtaining a fT>MIC of at least 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, and 100% was calculated for the β-lactams. The CFR of achieving a total AUC/MIC ratio greater than or equal to 75, 100, 125, 150, 175, 200, 225, and 250 was calculated for ciprofloxacin.12,25-27 In this analysis, bactericidal pharmacodynamic breakpoints were defined as fT>MIC of at least 40% for imipenem and meropenem, at least 50% for cefepime, ceftazidime, and piperacillin/tazobactam, and a total AUC/MIC ratio greater than or equal to 125 for ciprofloxacin.12,25,27-29 These breakpoints represent maximum bactericidal activity based on data obtained from in vitro animal and clinical pharmacodynamic studies.25,30 A bactericidal CFR greater than or equal to 90% was considered optimal; 95% confidence intervals were calculated around the bactericidal CFRs using the Wilson score method without continuity correction31 to determine the differences between agents.
Cumulative Fraction of Response
Table 3 lists the CFR at bactericidal pharmacodynamic target attainments for the various antimicrobial regimens. Imipenem (dosage, 1 g every 8 hours) was the only regimen to attain a bactericidal CFR greater than 90% against P. aeruginosa, although meropenem yielded a slightly lower value at 89%. Most of the β-lactam agents commonly used as first-line therapy against P. aeruginosa achieved similar bactericidal CFRs. For ceftazidime, an increase in dosage to 2 g every 8 hours raised the CFR to 82% from 73% of the 1-g dosing regimen administered every 8 hours. Between the 2 dosages simulated for piperacillin/tazobactam, the more frequent dosing regimen of 3.375 g administered every 4 hours yielded the highest CFR of 81%. Ciprofloxacin yielded the lowest CFR of 58%. Increasing the dose of this agent did not significantly improve the bactericidal CFR.
With respect to A. baumannii, no drug maintained bactericidal exposures greater than 90%. The highest CFRs were exhibited by imipenem (CFR, 83%) and meropenem (CFR, 70%). All remaining agents yielded bactericidal CFRs of less than or equal to 50%.
Against the Enterobacteriaceae, the ability to achieve bactericidal exposures was greater than 90% for all β-lactams tested. Of importance, dosages of ceftazidime (1 g every 8 hours), cefepime (1 g every 12 hours), and piperacillin/tazobactam (3.375 g every 6 hours) yielded adequate exposures such that the higher-dosing regimens used against P. aeruginosa were not necessary. The inability of ciprofloxacin (dosage, 400 mg every 12 hours) to yield equivalent CFRs to the β-lactams against E. coli is of utmost importance. Furthermore, increasing the dosage of ciprofloxacin to 400 mg every 8 hours did not improve the probability of achieving a bactericidal exposure.
Comparison of Susceptibilities Between 2002 and 2004 Data
The percentage of susceptibilities based on current CLSI breakpoints are listed for comparison in Table 4. Of interest is the significant decrease in P. aeruginosa susceptibilities to cefepime and piperacillin-tazobactam. Regarding A. baumannii, the increases in resistance are noted among all antimicrobials, most notably in imipenem and meropenem. In general, the resistance among the β-lactams against the Enterobacteriaceae has not progressed over the 2-year period. Resistant isolates against cefepime have now been observed in the 2004 data for E. coli and Klebsiella species because of the presence of ESBL-producing isolates that were not seen in the previous data. Lastly, of concern is the decrease in susceptibility of ciprofloxacin against E. coli, which has dropped from 92.6% in 2004 to 78.9% in 2002. The principal manifestation of this is an increase of isolates with MIC of 4 μg/mL (from 5.31% in 2002 to 20.7% in 2004). The resistance of fluoroquinolone against Klebsiella species has also increased, but to a far less extent.
Comparison of CFRs Between 2002 and 2004
A summary of the CFRs at bactericidal exposures is listed in Table 5. Against P. aeruginosa, changes in CFR occurred specifically for agents that had changes in percentage of susceptibility (ie, cefepime and ceftazidime). These agents had decreases in susceptibility of 6% and 2%, respectively, and had simultaneous decreases in CFR ranging from 7% to 14%, depending on the dosing interval simulated. In contrast, piperacillin/tazobactam susceptibilities decreased by 5.5% between 2002 and 2004, but a similar change in CFR was only observed with the 3.375-g regimen administered every 4 hours; no change in CFR was apparent with the regimen administered every 6 hours. Ciprofloxacin, imipenem, and meropenem CFRs did not change, largely because the percentage of susceptibilities remained similar between the years. For A. baumannii, the carbapenems, which retained a CFR near 90% in 2002, now have CFRs of 70% for meropenem and 83% for imipenem. Against E. coli and Klebsiella species, no significant differences were noted in comparing the CFRs, with the exception of ciprofloxacin. Against E. coli, a decrease in susceptibility of 13.7% resulted in a decreased CFR of 6%. However, a 3% decrease in susceptibility against Klebsiella species discordantly resulted in an increased CFR from 80% to 90%.
The current method of determining if an antibiotic retains its efficacy against a clinical pathogen of interest is through the use of standard susceptibility testing, which yields the antibiotic MIC. However, there are numerous limitations to the use of this method. First, actual MIC values are not reported in many hospitals, but only whether the organism is defined as susceptible, intermediate, or resistant according to CLSI-defined breakpoints. Although this information is meant to help the clinician interpret the microbiology data, these results provide no indication of the degree of susceptibility of a specific pathogen and leads to uncertainty in the most effective dose of antibiotic to administer. Other limitations include the poor correlation between defined susceptibility breakpoints and actual clinical outcomes largely due to the lack of incorporation of pharmacokinetic and pharmacodynamic data in the consideration of the antibiotic regimen and breakpoint chosen. This discordance was recently demonstrated by the shifting of the resistance breakpoint in ceftriaxone from 1 to 2 μg/mL against Streptococcus pneumoniae (for nonmeningeal infections) due to clinical and pharmacodynamic data, suggesting efficacy at the higher MIC despite being defined as resistant by the older NCCLS breakpoint.32
The OPTAMA program is meant to complement standard susceptibility testing and improve decision making for the clinician. Monte Carlo simulation is used to account for the interindividual variability in pharmacokinetic parameters among humans for each antibiotic and the MIC distribution specific to a geographic region to create thousands of different pharmacodynamic exposures obtained after administration of a specific antibiotic regimen. With the use of this method and with the incorporation of defined bactericidal breakpoints among the different antibiotic classes, the likelihood of achieving bactericidal exposures against specific pathogens of interest can be evaluated for different antimicrobial dosing regimens.
In this analysis, data are presented using MIC distributions obtained from the 2004 edition of the MYSTIC surveillance study in North America. Against P. aeruginosa, imipenem and meropenem retained the highest CFRs among all antibiotics tested. It was also noted that increasing doses and more frequent administration of agents originally attaining suboptimal CFRs (ie, low-dose cefepime, ceftazidime, and piperacillin/tazobactam) improved the relative performance of these β-lactams, but still did not achieve the optimal threshold (ie, 90% CFR). Ciprofloxacin demonstrated the lowest CFRs against P. aeruginosa. Because of the low probability of achieving a bactericidal exposure, caution is advised with the use of this agent as monotherapy against this pathogen. The reasons for these low CFRs include increasing resistance, as has been documented, for example, by Neuhauser et al33 and the lack of ability to achieve an AUC/MIC ratio of 125 when the MIC is greater or equal to 0.125 μg/mL for ciprofloxacin. Concerning A. baumannii, only imipenem retained marginal efficacy with a bactericidal CFR of 83%. Note that other noncarbapenem antibiotics used clinically to treat A. baumannii include sulbactam, tigecycline, doxycycline, and minocycline; however, the MYSTIC surveillance study does not report susceptibilities to these agents, so we were not able to test them. Against E. coli and Klebsiella species, 90% or greater CFRs were noted for all β-lactam agents at standard dosing regimens and at ciprofloxacin against Klebsiella species; however, the ciprofloxacin CFRs were significantly lower against E. coli (79%). Resistance to cefepime was observed in the 2004 edition of the MYSTIC antibiogram because 1.9% of the E. coli and 4.8% of Klebsiella species were confirmed ESBL-producers.13
To determine if significant changes in susceptibility affected changes in CFR, data were compared with those reported from 2002.10 As displayed in Table 4, 3 resistance trends predominate. The first is the decrease in susceptibility of all agents, along with a corresponding decrease in CFR against A. baumannii. Because the carbapenems are generally used at first line in combating these agents, significant decreases in CFRs at bactericidal exposures for both imipenem (−9%) and meropenem (−18%) are the most troubling (Table 5). Note that the MYSTIC surveillance study collects data from high-prescribing centers of meropenem, as compared with imipenem. Although specific usage data are not available, it is assumed that a bias toward increased meropenem resistance rates may result simply from greater usage. The second is the decreased susceptibility of certain β-lactams against P. aeruginosa, most notably cefepime and ceftazidime, the 2 cephalosporins most commonly used as first-line empirical treatment for serious nosocomial infections in many US hospitals. This translated into decreases in CFR of between 7% and 14% among the different cefepime- and ceftazidime-dosing regimens. The final trend is the dramatic decrease in susceptibility of ciprofloxacin to E. coli (92.6% in 2002; 78.9% in 2004), which led to a 6% decrease in CFR for the 400-mg regimen administered every 12 hours. These data are consistent with a previous report from another surveillance program in which only ciprofloxacin and levofloxacin susceptibility decreased in a stepwise manner from 1998 to 2001.34 These data also agree with a previous report documenting the increased ciprofloxacin resistance among Gram-negative bacilli, coupled with the concomitant increase in ciprofloxacin usage.33
Note that the absolute changes in the percentage of susceptibility for certain antibiotics, such as piperacillin/tazobactam and ciprofloxacin, did not necessarily result in the same numerical change in CFR. We speculate that this is due to incorrectly set susceptibility breakpoints for these agents. Whereas bactericidal exposure was not achieved even against organisms previously defined as susceptible, the subsequent declines in susceptibility for these drugs over the 2-year period did not result in further decreases in CFR because bactericidal exposure was already not attained against these organisms. One interesting observation was that there was a discordant increase in CFR from 80% in 2002 to 90% in 2004 although resistance increased from 1.4% to 4.8% for ciprofloxacin against Klebsiella species. The most conclusive explanation for this is displayed in Table 1. If the percentage of isolates at each MIC is evaluated, it is observed that an increase from 68.1% in 2002 to 90.4% in 2004 occurred at an MIC of 0.125 μg/mL. Furthermore, the MICs at 0.25 μg/mL and 0.5 μg/mL, which were 18.4% in 2002, now only constitute 3.3% of the total isolates. Although the MIC breakpoint for ciprofloxacin against Enterobacteriaceae is 1 μg/mL as defined by CLSI, the pharmacodynamic breakpoint that predicts a high likelihood of bactericidal exposures from these data is 0.125 μg/mL, which is consistent with a previous study suggesting lower clinical breakpoints for ciprofloxacin.35 At MICs greater than 0.125 μg/mL, an AUC/MIC ratio of 125 or greater is difficult to achieve with standard ciprofloxacin doses. These observations reiterate the importance of evaluating pharmacodynamic exposures on the basis of MIC distributions, in addition to percentage of susceptibility.
It is also imperative to note the assumptions made during these OPTAMA analyses. First, the MIC distributions constitute ICU only data from 14 institutions throughout North America. Non-ICU isolates (16 P. aeruginosa, 1 A. baumannii, 29 E. coli, and 30 Klebsiella species) were obtained from patients as well; however, they were excluded from this analysis because susceptibility data were not available for all antibiotics examined. Second, the pharmacokinetic parameters used were derived from healthy volunteers and not from critically ill patients. These data were used for consistency with the 2002 data because the main purpose of this analysis was to compare the CFRs over the 2-year period. Third, the use of the specific pharmacodynamic breakpoints that represent bactericidal exposures could be questioned. Some analyses suggest that different breakpoints should be used; for instance, in the case of cephalosporins, some reports suggest the need to achieve fT>MIC of 70% for maximal bactericidal activity, instead of the fT>MIC of 50% used in this analysis.29 Recent data has also suggested that breakpoints exist, which prevent the development of resistance from occurring, and these breakpoints are commonly higher than the currently accepted efficacy breakpoints used in this analysis.28 For these reasons, Figures 1, 2, and 3 are provided to examine the likelihood of achieving bactericidal exposures at various fTs >MIC or AUC/MIC ratios.
In comparison with 2002, the decrease in susceptibility among Gram-negative bacteria in North America correlated with a decreased pharmacodynamic CFR in most cases. This declining efficacy was most evident with ciprofloxacin against all pathogens, with special emphasis on E. coli. Against P. aeruginosa, the carbapenems should remain as the first-line empirical treatment for P. aeruginosa because of continued bactericidal exposures. The CFRs decreased drastically for all agents against A. baumannii, suggesting the need for combination therapy when empirically treating this pathogen. However, the discordant change observed for ciprofloxacin against Klebsiella species reiterates the importance of using OPTAMA methodology to complement the interpretation of microbiological surveillance studies. These data suggest that the continual evaluation of optimal dosing strategies for these antibiotics will be necessary because of the emerging resistance among nosocomial-acquired Gram-negative bacteria.
We would like to acknowledge Ronald N. Jones and the members of the Jones Group/JMI Laboratories (Iowa, USA) for performing susceptibility testing during the MYSTIC surveillance study, and Philip J. Turner of AstraZeneca (Cheshire, UK) for assistance with data management.
1. Karlowsky JA, Draghi DC, Jones ME, et al. Surveillance for antimicrobial susceptibility among clinical isolates of Pseudomonas aeruginosa
and Acinetobacter baumannii
from hospitalized patients in the United States, 1998 to 2001. Antimicrob Agents Chemother
2. Livermore DM. Multiple mechanisms of antimicrobial resistance in Pseudomonas aeruginosa
: our worst nightmare? Clin Infect Dis
3. Wisplinghoff H, Bischoff T, Tallent SM, et al. Nosocomial bloodstream infections in US hospitals: analysis of 24,179 cases from a prospective nationwide surveillance study. Clin Infect Dis
4. Rhomberg PR, Jones RN. Antimicrobial spectrum of activity for meropenem and nine broad spectrum antimicrobials: report from the MYSTIC Program (2002) in North America. Diagn Microbiol Infect Dis
5. Nijssen S, Florijn A, Bonten MJ, et al. Beta-lactam susceptibilities and prevalence of ESBL-producing isolates among more than 5000 European Enterobacteriaceae isolates. Int J Antimicrob Agents
6. Heffelfinger JD, Dowell SF, Jorgensen JH, et al. Management of community-acquired pneumonia in the era of pneumococcal resistance: a report from the Drug-resistant Streptococcus pneumoniae
Therapeutic Working Group. Arch Intern Med
7. Craig WA. Does the dose matter? Clin Infect Dis
. 2001;33(Suppl 3):S233-S237.
8. Nicolau DP. Optimizing outcomes with antimicrobial therapy through pharmacodynamic profiling. J Infect Chemother
9. Kiffer CR, Mendes C, Kuti JL, et al. Pharmacodynamic comparisons of antimicrobials against nosocomial isolates of Escherichia coli
, Klebsiella pneumoniae
, Acinetobacter baumannii
and Pseudomonas aeruginosa
from the MYSTIC surveillance program: the OPTAMA Program, South America 2002. Diagn Microbiol Infect Dis
10. Kuti JL, Nightingale CH, Nicolau DP. Optimizing pharmacodynamic target attainment using the MYSTIC antibiogram: data collected in North America in 2002. Antimicrob Agents Chemother
11. Masterton RG, Kuti JL, Turner PJ, et al. The OPTAMA programme: utilizing MYSTIC (2002) to predict critical pharmacodynamic target attainment against nosocomial pathogens in Europe. J Antimicrob Chemother
12. Forrest A, Nix DE, Ballow CH, et al. Pharmacodynamics of intravenous ciprofloxacin in seriously ill patients. Antimicrob Agents Chemother
13. Rhomberg PR, Fritsche TR, Sader HS, et al. Comparative antimicrobial potency of meropenem tested against Gram-negative bacilli: report from the MYSTIC surveillance program in the United States (2004). J Chemother
14. Clinical and Laboratory Standards Institute. Methods for Dilution Antimicrobial Susceptibilities Tests for Bacteria that Grow Aerobically-Fifteenth Informational Supplement.
Clinical and Laboratory Standards Institute: Wayne, PA; 2005, CLSI/NCCLS Document M100-S15.
15. Meyers BR, Srulevitch ES, Jacobson J, et al. Crossover study of the pharmacokinetics of ceftriaxone administered intravenously or intramuscularly to healthy volunteers. Antimicrob Agents Chemother
16. Pletz MW, Rau M, Bulitta J, et al. Ertapenem pharmacokinetics and impact on intestinal microflora, in comparison to those of ceftriaxone, after multiple dosing in male and female volunteers. Antimicrob Agents Chemother
17. Weidekamm E, Stoeckel K, Egger HJ, et al. Single-dose pharmacokinetics of Ro 17-2301 (AMA-1080), a monocyclic beta-lactam, in humans. Antimicrob Agents Chemother
18. Chow AT, Fowler C, Williams RR, et al. Safety and pharmacokinetics of multiple 750-milligram doses of intravenous levofloxacin in healthy volunteers. Antimicrob Agents Chemother
19. Dreetz M, Hamacher J, Eller J, et al. Serum bactericidal activities and comparative pharmacokinetics of meropenem and imipenem-cilastatin. Antimicrob Agents Chemother
20. Klepser ME, Patel KB, Nicolau DP, et al. Comparison of the bactericidal activities of ofloxacin and ciprofloxacin alone and in combination with ceftazidime and piperacillin against clinical strains of Pseudomonas aeruginosa. Antimicrob Agents Chemother
21. Mouton JW, Horrevorts AM, Mulder PG, et al. Pharmacokinetics of ceftazidime in serum and suction blister fluid during continuous and intermittent infusions in healthy volunteers. Antimicrob Agents Chemother
22. Nye KJ, Shi YG, Andrews JM, et al. Pharmacokinetics and tissue penetration of cefepime. J Antimicrob Chemother
23. Occhipinti DJ, Pendland SL, Schoonover LL, et al. Pharmacokinetics and pharmacodynamics of two multiple-dose piperacillin-tazobactam regimens. Antimicrob Agents Chemother
24. Mouton JW, Dudley MN, Cars O, et al. Standardization of pharmacokinetic/pharmacodynamic (PK/PD) terminology for anti-infective drugs: an update. J Antimicrob Chemother
25. Craig WA. Pharmacokinetic/pharmacodynamic parameters: rationale for antibacterial dosing of mice and men. Clin Infect Dis
26. Thomas JK, Forrest A, Bhavnani SM, et al. Pharmacodynamic evaluation of factors associated with the development of bacterial resistance in acutely ill patients during therapy. Antimicrob Agents Chemother
27. Wright DH, Brown GH, Peterson ML, et al. Application of fluoroquinolone pharmacodynamics. J Antimicrob Chemother
28. Drusano GL. Prevention of resistance: a goal for dose selection for antimicrobial agents. Clin Infect Dis
29. Turnidge JD. The pharmacodynamics of beta-lactams. Clin Infect Dis
30. DeRyke CA, Young Lee S, Kuti JL, et al. Optimising dosing strategies of antibacterials utilising pharmacodynamic principles: impact on the development of resistance. Drugs
31. Newcombe RG. Two-sided confidence intervals for the single proportion: comparison of seven methods Stat Med
32. Ambrose PG. Monte Carlo simulation in the evaluation of susceptibility breakpoints: predicting the future. Pharmacotherapy
33. Neuhauser MM, Weinstein RA, Rydman R, et al. Antibiotic resistance among gram-negative bacilli in US intensive care units: implications for fluoroquinolone use. JAMA
34. Karlowsky JA, Jones ME, Thornsberry C, et al. Trends in antimicrobial susceptibilities among Enterobacteriaceae isolated from hospitalized patients in the United States from 1998 to 2001. Antimicrob Agents Chemother
35. Montgomery MJ, Beringer PM, Aminimanizani A, et al. Population pharmacokinetics and use of Monte Carlo simulation to evaluate currently recommended dosing regimens of ciprofloxacin in adult patients with cystic fibrosis. Antimicrob Agents Chemother