Complicated skin and soft tissue infections (cSSTIs) are skin infections involving deeper soft tissue, and antimicrobial chemotherapy is usually required in addition to appropriate surgical interventions. Although gram-positive cocci, including Staphylococcus aureus, are the most common pathogens causing SSTIs, gram-negative bacilli and anaerobic bacteria can also be frequently involved, especially in mixed infections or if nosocomially acquired.1-3 Currently, cephalosporins and fluoroquinolones are among the most commonly used antibiotics for the empiric treatment of cSSTIs.4-6 However, rising resistance rates in both gram-positive and gram-negative bacteria have prompted the use of more broad-spectrum antibiotics, such as carbapenems and other antipseudomonal β-lactams. These agents not only cover Pseudomonas aeruginosa, which tends to cause more cSSTIs, but in the case of the carbapenems, also have improved activity against other drug-resistant bacteria, such as extended-spectrum β-lactamase producing Escherichia coli and Klebsiella pneumoniae. Among staphylococci, the prevalence of methicillin-resistant S. aureus (MRSA) is concerning; furthermore, community-acquired strains have now been documented as frequent causes of cSSTIs, even in patients without risk factors.7 None of the previously mentioned antibiotics have established activity against MRSA, making the decision for what to use empirically more difficult.
Given the complexity in considering resistance when choosing empiric therapy, as well as proper dosing, pharmacodynamic modeling has been proposed as a informative tool in the decision-making process for clinicians.8 The Optimizing Pharmacodynamic Target Attainment using Microbiology Antibiogram (OPTAMA) program aims at considering drug resistance (ie, minimum inhibitory concentration or MIC), pathogen frequency of different infection types, and antibiotic pharmacodynamics (ie, the dose needed to obtain a required bactericidal exposure) to improve clinical decision making.8 Pharmacodynamic studies have demonstrated that β-lactams kill bacteria best when free drug concentrations are maintained above the MIC for a critical time during the dosing interval, referred to as time above MIC (fT >MIC),9-11 whereas fluoroquinolones are concentration-dependent and kill best when their overall free drug exposure (area under the curve or AUC) is above the MIC (AUC/MIC) by approximately 30- to 100-fold.12-14
Past OPTAMA studies have evaluated the pharmacodynamics of mainly broad-spectrum antibiotics for the treatment of cSSTIs, intra-abdominal infections, and hospital-acquired pneumonia.15-17 In most situations, these agents performed optimally. However, it is important to compare the probability of optimal exposure of these broad-spectrum antibiotics with that of the more commonly used antibiotics, such as third-generation cephalosporins and fluoroquinolones, to determine if there is any benefit to their empiric use. In this study, we simulated the pharmacodynamic exposures of 9 different antibiotics against the pathogens most frequently causing SSTIs to determine which drug regimens would provide the greatest likelihood of obtaining bactericidal exposure for patients with cSSTIs given current resistance rates in the United States.
Antimicrobial Chemotherapy Regimens Simulated
Dosage regimens were chosen based on FDA indicated doses, and the most common regimens used in the United States for the treatment of SSTI are as follows: ceftazidime 1 g q8h, cefepime 1 g and 2 g q12h, ceftriaxone 1 g q24h, ciprofloxacin 400 mg q12h and q8h, ertapenem 1 g q24h, imipenem 500 mg and 1 g q8h, levofloxacin 500 mg and 750 mg q24h, meropenem 500 mg and 1 g q8h, and piperacillin-tazobactam 3.375 g q6h and 4.5 g q8h.
The pharmacodynamic exposures in serum for the β-lactam antibiotic regimens were simulated using a 1-compartment intravenous infusion model to calculate fT >MIC. All regimens were simulated as 30-minute infusions. For the fluoroquinolones, a noncompartmental approach was used to calculate the free drug AUC/MIC in serum.11-13,18 First, AUC was calculated by dividing the product of the fraction unbound and the 24-hour dose by the total body clearance (CLT). Then the AUC was divided by the MIC. In this analysis, bactericidal pharmacodynamic breakpoints were defined as a fT >MIC of at least 40% for meropenem, imipenem, and ertapenem; at least 50% for ceftazidime, cefepime, piperacillin-tazobactam, and ceftriaxone; and a free drug AUC/MIC ≥ 125 against gram-negative pathogens and ≥30 against gram-positive for ciprofloxacin and levofloxacin.9,10,13,14,18,19 We assumed that serum concentrations would be similar to exposure attained at the site of infection in a subject with a cSSTI.
Estimates of pharmacokinetic parameters and their dispersion used in the model were extrapolated from published healthy volunteer studies or as reported from previous OPTAMA simulations.20-24 The means and standard deviations for CLT and volume of distribution (V d) used in these analyses are listed in Table 1. During simulations, these pharmacokinetic parameters were assumed to follow a log-Gaussian distribution. The unbound fraction (f u) of all tested drugs was taken from the package inserts or from the previous studies noted, and was assumed to follow a uniform distribution with an equal probability of occurrence within the specified range of the distribution.
Minimum inhibitory concentration values were derived for isolates obtained in North America during the 2004 version of Meropenem Yearly Susceptibility Test Information Collection (MYSTIC) Program.25 Fifteen centers across the United States and 3 institutions in Canada participated in the North American region of the 2004 MYSTIC program. A total of 160 Enterobacter species, 724 Escherichia coli, 430 Klebsiella species, 689 Pseudomonas aeruginosa, and 68 S. aureus (methicillin-susceptible S. aureus [MSSA] only) having susceptibility data for all desired antibiotics were collected (Table 2). Duplicated isolates of the same patient and from the same origin were excluded. MICs were conducted by broth microdilution or E-test as previously described.25 Isolates from all sources were included because of the sparse selection of bugs collected specifically from cSSTI sources.
Monte Carlo Simulation
Pharmacodynamic simulations were conducted via Monte Carlo simulation (Crystal Ball 2000; Decisioneering, Denver, Colo). This method of analysis is based on artificially recreating a chance process, running it many times, and directly observing the results. When run enough times, the probability of any specific target can be easily calculated from the population of results.8 For each antibiotic regimen/pathogen combination, a 5000-subject Monte Carlo simulation was conducted to estimate the range of fT >MIC for the β-lactams and free AUC/MIC for the fluoroquinolones. During each iteration, unique scenarios of exposure possibilities based on pharmacokinetic parameter variability (CLT, V d, and f u) and MIC distributions were calculated and plotted on a frequency distribution curve for analysis. From each frequency distribution plot, the bactericidal cumulative fraction of response (CFR) was calculated. The CFR is the expected probability of target attainment for a specific drug and dose against a specific population of microorganisms.21 Bactericidal exposure targets were defined as the following: 40% fT >MIC for ertapenem, imipenem, and meropenem against all bacteria; 50% fT >MIC for the remaining β-lactams against all bacteria; a free AUC/MIC ratio ≥30 for ciprofloxacin and levofloxacin against the gram-positive bacteria; and a free AUC/MIC ratio ≥125 for ciprofloxacin and levofloxacin against the gram-negative bacteria.
The CFR for each drug regimen/pathogen population was then weighted by the prevalence of the top 5 pathogens causing cSSTIs as reported in the 2000 SENTRY Antimicrobial Surveillance report.2 The adjusted prevalence of the top 5 pathogens from this report were S. aureus (61.6%), followed by P. aeruginosa (14.5%), E. coli (9.5%), Enterobacter species (7.7%), and Klebsiella species (6.7%). The final weighted CFR represents the likelihood that any drug regimen will attain bactericidal pharmacodynamic exposure for the empiric treatment of cSSTIs, assuming pharmacokinetic parameter variability, current resistance rates as reported in the 2004 MYSTIC Program (excluding MRSA), and the prevalence of pathogens consistent with the SENTRY report. A CFR ≥90% was considered optimal for empiric therapy.21 Confidence intervals for CFR proportions were calculated at α = .05 using the Newcombe-Wilson method without correction for continuity.26 Statistical significance was evaluated using the χ2 method for a difference between 2 proportions (SigmaStat 2.0.3, Chicago, IL).
After initial models were completed, we performed a sensitivity analysis to consider the effect of MRSA rates on the pharmacodynamic exposures of these antibiotics. We reran all simulations, each time increasing the rate of MRSA in 10% increments between 10% and 50%.
Bactericidal CFR by Pathogen
Table 3 demonstrates bactericidal CFR for each antibiotic dosing regimen (in alphabetical order) against each population of bacteria. Cefepime performed optimally against E. coli, Enterobacter spp., Klebsiella spp., and MSSA, but only at the higher dose for the latter organism. CFR against P. aeruginosa was also significantly better with the higher dose (83.2% vs. 66.5%, P < 0.001). Ceftazidime and ceftriaxone performed optimally only against the populations of E. coli and Klebsiella spp. In particular, MSSA was problematic for both of these antibiotics; furthermore, as suspected, ceftriaxone attained only 2.4% CFR against P. aeruginosa.
Ciprofloxacin and levofloxacin performed similarly for the gram-negative organisms, although no regimen attained greater than 90% CFR against any population with the exception of higher doses (400 mg q8h and 750 mg q24h, respectively) against the Klebsiella spp. Against S. aureus, levofloxacin performed significantly better than ciprofloxacin, but still achieved only 79.1% CFR at the 750-mg dose. In contrast, ciprofloxacin performed better against P. aeruginosa when comparing the high doses (58.1% vs. 41.3%, P < 0.001).
Standard doses of imipenem and meropenem (ie, 1 g q8h) were the only antibiotics to attain at least 90% CFR against all bacterial populations, although the meropenem CFR was slightly less (89.3%), but not significantly different from that of imipenem. There were no significant differences between CFR for the 500-mg q8h regimens also; however, CFR against P. aeruginosa was reduced to 86.1% for imipenem and 84.4% for meropenem. Ertapenem also performed competitively with the other carbapenems against all pathogens except P. aeruginosa, where CFR was only 28.5%. Lastly, piperacillin-tazobactam regimens achieved greater than 90% CFR against S. aureus, E. coli, and Klebsiella spp., but only with the q6h regimen for the latter organism. CFR was significantly lower against P. aeruginosa (69.8% for the q6h regimen and 53.9% for the q8h regimen) and Enterobacter spp. (82.5% and 73.9%, respectively). In all cases, the 3.375-g q6h regimen achieved significantly greater CFR compared with the 4.5-g q8h regimen (P < 0.001).
Bactericidal CFR Weighted by Pathogen Prevalence for cSSTIs
The bactericidal CFRs for each antibiotic dosing regimen when weighted by the prevalence of the top 5 pathogens causing cSSTIs are listed in Table 4. Only cefepime 2 g q12h, all imipenem and meropenem dosing regimens, and piperacillin-tazobactam 3.375 g q6h achieved greater than 90% likelihood of bactericidal CFR. The rank order of performance was: imipenem 1 g q8h, meropenem 1 g q8h, imipenem 500 mg q8h, meropenem 500 mg q8h, cefepime 2 g q12h, and piperacillin-tazobactam 3.375 g q6h. The next highest regimens were ertapenem (87.8%) and piperacillin-tazobactam (86.8%), both of which suffered because of their less than optimal CFR against potential P. aeruginosa. Finally, the remaining antibiotics achieved significantly lower weighted CFRs, with ceftriaxone and ceftazidime regimens achieving less than a 50% likelihood of empirically attaining bactericidal exposure against the most common pathogens associated with cSSTIs and the fluoroquinolones achieving between 55.3% and 75.1% CFR.
Sensitivity Analysis for Rate of MRSA
Resimulations for all drug regimens with increasing rates of MRSA within the S. aureus population demonstrated that CFR for all regimens decreased proportionally (Fig. 1). Only 1-g q8h regimens of imipenem and meropenem maintained CFR above 90% until MRSA rates approached greater than 10%.
The decision to use a specific antibiotic regimen empirically for a cSSTI is often made based on an attempt to cover the most likely bacterial causes, along with consideration of local resistance patterns. Although this approach is routinely adequate, these factors do not inform the clinician what the optimal dose is to maximize the probability of killing the organism. The OPTAMA program incorporates current susceptibility data of targeted pathogens with pharmacokinetic parameter variability to determine the probability of achieving bactericidal exposure for the treatment of specific pathogens or types of infections. The present study was aimed at determining the likelihood of typical empiric antimicrobial regimens attaining bactericidal exposure against common pathogens implicated in cSSTIs. Accordingly, cefepime 2 g q12h, imipenem 500 mg and 1 g q8h, meropenem 500 mg and 1 g q8h, and piperacillin-tazobactam 3.375 g q6h provided acceptably high CFRs and would be optimal therapeutic regimens for the empiric treatment of cSSTIs, excluding coverage of MRSA. In contrast, because of increasing resistance and poor pharmacodynamic attainment with currently used dosages, third-generation cephalosporins and both fluoroquinolones were inferior to the more broad-spectrum antibiotics.
Because of their favorable safety profile, low cost, and ease of use, cephalosporins are among the most popular choices for the empiric treatment of cSSTIs. Despite this, the present analysis demonstrated that third-generation cephalosporins had the lowest CFRs among the tested antimicrobials. It was clear to see that antibiotics such as ceftriaxone and ceftazidime are not able to achieve bactericidal pharmacodynamic exposure against many of the chief players in cSSTIs, namely, S. aureus (even methicillin-susceptible strains). If combined with an antibiotic that has activity against both MRSA and MSSA strains such as vancomycin, the CFR for these agents would certainly increase, but high MIC values among common gram-negatives such as P. aeruginosa, Enterobacter, and even some E. coli, suggest that they would still not be optimal choices for empiric therapy of cSSTIs. In contrast, cefepime performed well against MSSA and most of the implicated gram-negatives. Because of this, agents improved potency; it might be the only cephalosporin that is suitable for empiric therapy of cSSTIs. However, one important finding that susceptibility studies would have otherwise missed was that the low-dose cefepime regimen, which is indicated for mild to moderate infections, clearly performed less optimally against S. aureus and P. aeruginosa strains. Based on pharmacodynamic modeling, the use of a higher dose would be necessary in the absence of another antistaphylococcal antibiotic, or when P. aeruginosa is suspected. Although we did not analyze higher cefepime doses, other OPTAMA studies have demonstrated that a regimen of 2 g q8h achieves among the highest CFR against current P. aeruginosa isolates in the United States.16
Another popular choice for the empiric treatment of cSSTIs is an agent from the fluoroquinolone class.1 According to a recent review by Martin and Zeigler,27 the fluoroquinolones were as effective as β-lactam antibiotics in managing a spectrum of skin infections including erysipelas, cellulitis, impetigo, surgical wounds, and diabetic foot infections. However, more recent studies have documented the alarming rise in resistance among gram-negatives associated with the overuse of this class.28 This is most apparent among P. aeruginosa and E. coli in the United States.29 From a pharmacodynamic perspective, these agents are predicted to perform worse than the reported percent susceptibility against gram-negatives due to the inability to achieve AUC/MIC ratios greater than 125 for all bacteria reported as susceptible, given the currently used dosages.30 In this analysis, ciprofloxacin and levofloxacin performed quite similarly, with ciprofloxacin better for P. aeruginosa (58.1% vs. 41.3%) and levofloxacin better for S. aureus (79.1% vs. 67.7%). However, although there were certainly differences within the class, both agents overall achieved lower CFRs when compared with the more broad-spectrum β-lactams. An especially alarming concern is the increasing MICs against E. coli, a common pathogen in cSSTIs among other infection types, which resulted in less than optimal CFR for both agents in this analysis.29,31
Ertapenem, a broad-spectrum once-daily carbapenem, is also approved for the treatment of cSSTIs, demonstrating equivalent effectiveness to piperacillin-tazobactam in clinical trials.32,33 From a pharmacodynamic perspective, ertapenem would be an optimal antibiotic for the empiric treatment of cSSTIs, but only when suspicion of P. aeruginosa is very low. The low CFR for ertapenem against this nonfermentor (28.5%) resulted in its less than optimal CFR for empiric treatment (87.8%).
A notable concern for the treatment of cSSTIs is the increasing prevalence of MRSA, both in the hospital and in the community setting. The National Nosocomial Infections Surveillance (NNIS) System reported that the prevalence of MRSA was almost 57.1% in intensive care units and 51.60% outside of the unit among isolated S. aureus from 1998 through 2003.28 None of the antimicrobials tested could achieve adequate CFRs for the management of SSTIs once the rate of MRSA extended beyond 10% (Fig. 1). As a result, the concomitant use of an antibiotic that has activity against this phenotype, such as vancomycin, linezolid, or daptomycin, among others, would be justified empirically. The MYSTIC surveillance study did not contain MIC data for these agents, and therefore, we could not simulate pharmacodynamic attainment against the MRSA isolates. Furthermore, the recent approval of tigecycline, a drug that has activity against both gram-positives (including MRSA) and many gram-negatives, provides an additional choice for the treatment of cSSTIs.1 Further pharmacodynamic comparative studies are needed to assess the relative performance of this new agent with that of the broad-spectrum β-lactams found to be superior in this simulation.
Because we are recommending the empiric use of broad-spectrum antibiotics (cefepime, imipenem, meropenem, and piperacillin-tazobactam) plus an anti-MRSA agent for the treatment of cSSTIs, we should stress that overuse of these antibiotics also will lead to the eventual development of resistance. De-escalation to a narrow-spectrum antibiotic, or discontinuation altogether, is encouraged once culture and susceptibility data are available or if the patient has improved. The optimal use of empiric therapy, together with the de-escalation concept and shorter courses, should result in the most appropriate antibiotic stewardship and delay the emergence of resistance to these broad-spectrum agents.
It is important to note the assumptions we used in this analysis, as this will allow for greater interpretation of the results in one's specific practice. First, the susceptibility data in the MYSTIC program come from isolates collected at various sites (wound, sputum, blood, urine, etc). Only 10% of the isolates in this study were derived from potential cSSTIs; furthermore, pathogens causing cSSTIs may have different susceptibility patterns from other sites, especially P. aeruginosa isolates. The small numbers of isolates from wound sources limited us in our ability to only simulate exposures against these isolates; therefore, our results might represent a worse-case scenario. Secondly, some clinical trials report species of streptococci as a common cause of cSSTIs.32,34 Streptococci were not among the top 5 pathogens causing cSSTIs in the SENTRY report, probably because most of these isolates were derived from patients who acquired their cSSTIs in the hospital (ie, surgical site infections).2 Thus, our results are likely better suited for nosocomial acquired cSSTIs than less complicated skin infections developing in the community. Furthermore, few laboratories currently conduct susceptibility testing on S. pyogenes in the United States, as they remain quite susceptible to standard therapies.35 Enterococcus was also excluded from this analysis due to the continued controversy regarding its clinical impact as a primary pathogen in polymicrobial skin and intra-abdominal infections.36,37 Lastly, we should point out that our results should be applicable to most patients with cSSTIs. However, any specific infection type, for example, diabetic ulcers, might lend to varied clinical results depending on the location of the infection (distal vs proximal) and the amount of peripheral vascular disease. Lastly, we acknowledge that the need for adjunctive surgical interventions (incision and drainage) might be necessary in certain cSSTIs and was not accounted for in our model.
When considering current resistance patterns and the prevalence of pathogens causing cSSTIs, this pharmacodynamic analysis demonstrated that optimally dosed regimens of broad-spectrum antibiotics (cefepime, imipenem, meropenem, and piperacillin-tazobactam), in combination with an antibiotic targeting MRSA, will provide the greatest likelihood of achieving bactericidal exposures for the empiric treatment of cSSTIs. In contrast, the routine use of third-generation cephalosporins and fluoroquinolones in cSSTIs should be discouraged due to emerging resistance and poor pharmacodynamic performance.
We thank Ronald N. Jones and 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 his assistance with data management.
1. Lee SY, Kuti JL, Nicolau DP. Antimicrobial management of complicated skin and skin structure infections in the era of emerging resistance. Surg Infect (Larchmt)
2. Rennie RP, Jones RN, Mutnick AH. Occurrence and antimicrobial susceptibility patterns of pathogens isolated from skin and soft tissue infections: report from the SENTRY Antimicrobial Surveillance Program (United States and Canada, 2000). Diagn Microbiol Infect Dis
3. Doern GV, Jones RN, Pfaller MA, et al. Bacterial pathogens isolated from patients with skin and soft tissue infections: frequency of occurrence and antimicrobial susceptibility patterns from the SENTRY Antimicrobial Surveillance Program (United States and Canada, 1997). SENTRY Study Group (North America). Diagn Microbiol Infect Dis
4. Tack KJ, Keyserling CH, McCarty J, et al. Study of use of cefdinir versus cephalexin for treatment of skin infections in pediatric patients. The Cefdinir Pediatric Skin Infection Study Group. Antimicrob Agents Chemother
5. Tack KJ, Littlejohn TW, Mailloux G, et al. Cefdinir versus cephalexin for the treatment of skin and skin-structure infections. The Cefdinir Adult Skin Infection Study Group. Clin Ther
6. Karchmer AW. Fluoroquinolone treatment of skin and skin structure infections. Drugs
. 1999;58(suppl 2):82-84.
7. Fridkin SK, Hageman JC, Morrison M, et al. Methicillin-resistant Staphylococcus aureus
disease in three communities. N Engl J Med
8. Kuti JL, Nicolau DP. Making the most of surveillance studies: summary of the OPTAMA Program. Diagn Microbiol Infect Dis
. 2005;53(4): 281-287.
9. Drusano GL. Prevention of resistance: a goal for dose selection for antimicrobial agents. Clin Infect Dis
. 2003;36(suppl 1):S42-S50.
10. Turnidge JD. The pharmacodynamics of beta-lactams. Clin Infect Dis
11. Craig WA. Pharmacokinetic/pharmacodynamic parameters: rationale for antibacterial dosing of mice and men. Clin Infect Dis
. 1998;26(1):1-10; quiz 11-2.
12. Madaras-Kelly KJ, Ostergaard BE, Hovde LB, et al. Twenty-four-hour area under the concentration-time curve/MIC ratio as a generic predictor of fluoroquinolone antimicrobial effect by using three strains of Pseudomonas aeruginosa
and an in vitro pharmacodynamic model. Antimicrob Agents Chemother
13. Forrest A, Nix DE, Ballow CH, et al. Pharmacodynamics of intravenous ciprofloxacin in seriously ill patients. Antimicrob Agents Chemother
14. Wright DH, Hovde LLB, Peterson ML, et al. In vitro evaluation of pharmacodynamic outcome parameters for three fluoroquinolones against Streptococcus pneumoniae. In: Program and Abstract of the Ninety-Eighth General Meeting, Atlanta, GA, 1998. Abstract 85, p.53. American Society for Microbiology, Washington, DC; 1998.
15. Ong CT, Kuti JL, Nicolau DP. Pharmacodynamic modeling of imipenem-cilastatin, meropenem, and piperacillin-tazobactam for empiric therapy of skin and soft tissue infections: a report from the OPTAMA Program. Surg Infect (Larchmt)
16. Sun HK, Kuti JL, Nicolau DP. Pharmacodynamics of antimicrobials for the empirical treatment of nosocomial pneumonia: a report from the OPTAMA Program. Crit Care Med
17. Kotapati S, Kuti JL, Nicolau DP. Pharmacodynamic modeling of beta-lactam antibiotics for the empiric treatment of secondary peritonitis: a report from the OPTAMA program. Surg Infect (Larchmt)
18. Wright DH, Brown GH, Peterson ML, et al. Application of fluoroquinolone pharmacodynamics. J Antimicrob Chemother
19. Craig WA. Pharmacokinetic/pharmacodynamic parameters: rationale for antibacterial dosing of mice and men. Clin Infect Dis
20. 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
21. Kuti JL, Nightingale CH, Nicolau DP. Optimizing pharmacodynamic target attainment using the MYSTIC antibiogram: data collected in North America in 2002. Antimicrob Agents Chemother
22. 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
23. 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
24. Hoffken G, Lode H, Prinzing C. et al. Pharmacokinetics of ciprofloxacin after oral and parenteral administration. Antimicrob Agents Chemother
25. 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
26. Newcombe RG. Two-sided confidence intervals for the single proportion: comparison of seven methods. Stat Med
27. Martin SJ, Zeigler DG. The use of fluoroquinolones in the treatment of skin infections. Expert Opin Pharmacother
28. National Nosocomial Infections Surveillance (NNIS) System Report, data summary from January 1992 through June 2004, issued October 2004. Am J Infect Control
29. Neuhauser MM, Weinstein RA, Rydman R, et al. Antibiotic resistance among gram-negative bacilli in US intensive care units: implications for fluoroquinolone use. JAMA
30. 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
31. MacDougall C, Powell JP, Johnson CK, et al. Hospital and community fluoroquinolone use and resistance in Staphylococcus aureus
and Escherichia coli
in 17 US hospitals. Clin Infect Dis
32. Graham DR, Lucasti C, Malafaia O, et al. Ertapenem once daily versus piperacillin-tazobactam 4 times per day for treatment of complicated skin and skin-structure infections in adults: results of a prospective, randomized, double-blind multicenter study. Clin Infect Dis
33. Invanz (Ertapenem) package insert. Merck, NJ: Merck & Co.; 2004.
34. Ellis-Grosse EJ, Babinchak T, Dartois N, et al. The efficacy and safety of tigecycline in the treatment of skin and skin-structure infections: results of 2 double-blind phase 3 comparison studies with vancomycin-aztreonam. Clin Infect Dis
. 2005;41(suppl 5):S341-S353.
35. Stevens DL, Bisno AL, Chambers HF, et al. Practice guidelines for the diagnosis and management of skin and soft-tissue infections. Clin Infect Dis
36. Nichols RL, Muzik AC. Enterococcal infections in surgical patients: the mystery continues. Clin Infect Dis
37. Harbarth S, Uckay I. Are there patients with peritonitis who require empiric therapy for enterococcus? Eur J Clin Microbiol Infect Dis