Fluoroquinolone-resistant Pseudomonas aeruginosa: risk factors for acquisition and impact on outcomes

Donald I. Hsu1,2, Mark P. Okamoto3, Rekha Murthy4 and Annie Wong-Beringer1,2,*

1 School of Pharmacy, University of Southern California, 1985 Zonal Avenue, Los Angeles, CA 90033; 2 Department of Pharmacy, Huntington Hospital, Pasadena, CA; 3 College of Pharmacy, Western University, Pomona, CA; 4 Department of Hospital Epidemiology, UCLA David Geffen School of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA


* Corresponding author. Tel: +1-323-442-1356; Fax: +1-626-628-3024; Email: anniew{at}usc.edu

Received 20 October 2004; returned 24 November 2004; revised 8 December 2004; accepted 20 December 2004


    Abstract
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Objectives: Resistance among Pseudomonas aeruginosa has risen dramatically and parallels the increase in fluoroquinolone (FQ) prescribing in recent years. Risk factors for FQ resistance in P. aeruginosa and its impact on outcomes need to be well characterized.

Methods: A case–control study was carried out on hospitalized adult patients from whom FQ-resistant (case) and FQ-susceptible (control) P. aeruginosa were isolated.

Results: A total of 177 patients with positive cultures (91 cases and 86 controls) and 119 with documented infections (65 cases, 54 controls) were included in risk factor and outcomes analysis, respectively. Independent risk factors for FQ resistance were: FQ exposure (OR 12.6, CI 4.95–32), nosocomial acquisition (OR 8.6, CI 3.5–20.7), and diabetes mellitus (OR 6.4, CI 2.1–19.3). An FQ agent was prescribed in 59% of patients receiving an ‘antipseudomonal’ empirical regimen. Compared with controls, FQ-resistant cases had a median delay to receiving effective therapy of 3.5 days versus 1 day and poorer outcomes: (i) lower complete response rate (45% versus 63%, P=0.04); (ii) longer time to achieve clinical stability (8 days versus 3 days, P=0.005); and (iii) higher infection-related mortality (21% versus 7%; OR = 2.9, 0.9–9.4). Empirical FQ use (OR 4.6, CI 1.5–14.3), FQ resistance (OR 3.6, CI 1.0–13.1), and high APACHE II score (OR 1.1, CI 1.0–1.2) were independent risk factors for increased mortality.

Conclusions: FQ exposure from widespread prescribing is a modifiable risk factor for FQ resistance in P. aeruginosa. FQ empirical therapy for Pseudomonas infections may be associated with significant delays in administering effective therapy resulting in adverse outcomes.

Keywords: levofloxacin , empirical prescribing , multidrug resistance , mortality


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According to the National Nosocomial Infections Surveillance (NNIS) System, Pseudomonas aeruginosa is among the leading pathogens causing nosocomial infections and is the most common cause of pneumonia in the medical ICU.1 Managing infections caused by P. aeruginosa is a clinical challenge due to the bacteria's intrinsic as well as remarkable ability to acquire antibiotic resistance.2,3 Antimicrobial agents with reliable anti-pseudomonal activity that are commonly prescribed are limited to only a few agents in three major pharmacological classes: lactams, fluoroquinolones (FQs) and aminoglycosides.4 Among these, the FQs provide the only available oral treatment option. The introduction of new-generation FQ agents with enhanced activity against respiratory pathogens and favourable pharmacokinetic and safety profiles has led to widespread prescribing of this class of agents in recent years.5

Paralleling the widespread use of the FQ class is an alarming increase in the prevalence of FQ resistance (FQ-R) among P. aeruginosa strains. In US intensive care units, the rate of P. aeruginosa resistance to ciprofloxacin tripled from 11% during 1990–93 to 32% in 2000.6 The increase in resistance was significantly associated with increased national use of FQs in this study6 as well as others.7,8 More importantly, resistance to ciprofloxacin was significantly associated with cross-resistance to other antimicrobial agents.6

Several investigators have examined the risk factors for emergence of antibiotic-resistant P. aeruginosa and associated outcomes.911 However, the risk factors for acquisition and impact of infections caused specifically by FQ-R P. aeruginosa strains on outcomes are unknown. In the present setting of rising Pseudomonas resistance to the FQs, widespread empirical use of FQs may adversely affect treatment outcomes. Therefore, we investigated the risk factors associated with acquisition of FQ-R P. aeruginosa and the impact of resistance on patient outcomes.


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Study design and microbiology

We carried out a case–control study at Huntington Hospital, a 525 bed community teaching hospital in Pasadena, CA, USA. The study protocol was approved by the hospital's Institution Review Board.

The microbiology laboratory computer records were used to identify all hospitalized adult patients from whom P. aeruginosa was isolated during the period May 2001–July 2002. Eligible patients were designated as cases or controls based solely by FQ susceptibility of the isolated P. aeruginosa strain. P. aeruginosa was identified by its characteristic positive oxidase reaction and blue-green pigmentation and with the use of the Gram-Negative Identification Panel (Vitek, BioMérieux, Hazelwood, MO, USA). In vitro susceptibility testing was carried out by microbroth dilution (Vitek, BioMérieux) and results interpreted according to NCCLS guidelines.12 The agents tested were: piperacillin–tazobactam, ceftazidime, cefepime, imipenem, gentamicin, tobramycin and amikacin. Resistance included strains with intermediate susceptibility. Specifically, FQ-R included strains with ciprofloxacin MIC ≥ 2 mg/L and levofloxacin MIC ≥ 4 mg/L. Ciprofloxacin was used as a marker for susceptibility for all FQ antibiotics since cross-resistance between ciprofloxacin and levofloxacin was demonstrated for all strains.

Definitions and data collection

The medical and laboratory records for eligible patients were reviewed. Exclusion criteria were receipt of any investigational agents within 10 days and cystic fibrosis. Pertinent demographic, laboratory, radiographic and clinical data were obtained and recorded onto a structured form. APACHE II score was calculated for all patients at the time of admission to assess severity of underlying illness. The data were then compiled into a single data set using a relational database management system (Microsoft Access).

Multidrug resistance (MDR) was defined as resistance to ≥ 2 classes of anti-pseudomonal agents. For the purpose of study analysis, each of the following represents a ‘unique’ class: piperacillin–tazobactam, ceftazidime/cefepime, imipenem, ciprofloxacin/levofloxacin, and gentamicin/tobramycin/amikacin.

Risk factor analysis

For risk factor analysis, each patient was included as a case or control only once. Analysis included patients who were either colonized or infected with P. aeruginosa. The following data were obtained: age, gender, prior FQ exposure, place of residence before isolation of P. aeruginosa, and comorbid conditions. FQ use within 30 days preceding the first isolation of P. aeruginosa was documented if noted in the patient's medical record. FQ exposure was assessed by the specific agent used and the duration of use. Comorbid conditions included: diabetes mellitus, coronary artery disease, cerebrovascular disease, pulmonary disease (asthma, COPD), hepatic dysfunction (total bilirubin > 2.5 mg/dL or 42.75 µmol/L, ALT/AST > 2x normal limits, or known liver disease); renal insufficiency (serum creatinine > 2.0 mg/dL or 34.2 µmol/L), HIV infection, malignancy, prior transplantation, neutropenia ( < 500 cells/mm3), corticosteroid use (prednisolone ≥ 20 mg/day or equivalent), use of an immunosuppressive agent within 30 days.

Outcomes analysis

For outcome analysis, only the first episode of infection was reviewed if P. aeruginosa had been isolated on multiple occasions within a 6 month period. Analysis included only patients who had a documented infection defined by criteria established by the CDC13 and had completed ≥ 72 h of antibiotic therapy. Nosocomial infections were defined as those acquired in a nursing home or ≥ 48 h after hospital admission. Six outcomes were examined: (i) time to achieve clinical stability; (ii) delay to effective treatment; (iii) treatment response; (iv) length of stay after isolation; (v) total length of hospital stay; and (vi) death (where applicable) attributable to the P. aeruginosa infection.

Time to achieve clinical stability was defined as the time (days) required for return of abnormal vital signs to normal baseline values (heart rate ≤ 100 beats/min, systolic blood pressure ≥ 90 mmHg, respiratory rate ≤ 24 breaths/min, oxygen saturation ≥ 90%, and maximum temperature ≤ 37.2°C), extubation, and return of mental status to baseline. The specific antimicrobial agent(s) used and the total duration of treatment were recorded. A regimen was considered effective if it contained at least one agent active against the isolated P. aeruginosa strain. The interval between the time of culture samples and the time effective antibiotics were administered was measured as the delay in effective therapy. An antibiotic was considered effective if the P. aeruginosa strain isolated demonstrated in vitro susceptibility to it. Response was defined as resolution or improvement of fever, leucocytosis, and local signs of infection, and non-response as failure (absence of resolution or worsening of signs and symptoms of infection) or relapse (recurrence of infection with same organism at any body site within a month after discontinuation of therapy).

Statistical analysis

Statistical analyses were carried out with BMDP Dynamic Release version 7.0 and SPSS version 11.0 (Chicago, IL, USA), or GraphPad Prism version 4.0 (San Diego, CA, USA). Case and control variables were compared using Student's t-test, Mann–Whitney U-test, {chi}2 or Fisher's exact test where applicable. Logistic regression was used to identify associations between the independent variables tested and the dichotomous dependent variables in the multivariate analysis.

Survival analysis was conducted using the Kaplan–Meier method and the log-rank test. Time 0 began at the time effective therapy for P. aeruginosa infections was initiated. Patients were censored at day 14 or death.

All statistical tests were two-tailed; P ≤ 0.05 was considered significant.


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A total of 253 potential cases and controls were identified from the microbiology laboratory records. Evaluable patients (cases and controls) for risk factor and outcome analyses were 177 and 119, respectively (Figure 1).



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Figure 1. Study population. Cases, fluoroquinolone-resistant; controls, fluoroquinolone-susceptible.

 
Characteristics of the cases and controls are shown in Table 1. Study patients represented an elderly population (mean age, 71 ± 16.5 years) with nearly half of them (47%, 83/177) resident in the community before hospital admission. Many of the patients had severe underlying illness (mean APACHE II score, 14 ± 6.7) and multiple co-morbidities (mean, 2.6 ± 1.7). The majority of isolates from evaluable patients were obtained from the respiratory tract (n=67/177, 38%) and urine (n=62/177, 35%), followed by wound (n=38/177, 22%), and blood (n=10/177, 5%).


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Table 1. Risk factors for FQ resistance

 
Risk factor analysis

Several risk factors were found to be significantly associated with the acquisition of FQ-R P. aeruginosa by both univariate and multivariate analyses with odds ratio ranging from 6.4 to 12.6: nosocomial residence, diabetes as a co-morbid condition, and exposure to an FQ within 30 days before isolation of organism (Table 1).

Data on quinolone exposure within 30 days preceding isolation of P. aeruginosa were available for the majority of the patients (84%, 149/177); however, outpatient antibiotic therapy before admission was unclear for the remaining 28 patients. Levofloxacin was the agent most commonly prescribed for those with prior FQ exposure. The median duration of FQ use was 6 days, which did not differ between study groups. It is notable that detailed analysis on the extent of exposure was not possible due to the inconsistent documentation in the chart with respect to agent prescribed, dose and duration.

Microbiological characteristics

Susceptibility patterns of the initial P. aeruginosa isolates from all patients were examined by drug classes and agents within each class (Table 2 and Figure 2). FQ-R was significantly associated with MDR phenotype. Logistic regression analysis identified the following independent risk factors for MDR phenotype: ciprofloxacin resistance (OR 12.6, CI 5.2–30.6), prior FQ exposure (OR 2.6, CI 1.1–6.5), and underlying pulmonary disease (OR 2.5, CI 1.1–5.8). Susceptibility patterns did not vary by specimen source (data not shown).


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Table 2. Antimicrobial cross-resistance pattern

 


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Figure 2. Comparison of the cross-resistance pattern of FQ-R versus FQ-S isolates. P < 0.05 for all comparisons. FQ-R, fluoroquinolone-resistant (cases); FQ-S, fluoroquinolone-susceptible (controls); MDR, multidrug resistance (resistance to two or more classes of anti-pseudomonal agents: piperacillin–tazobactam, ceftazidime/cefepime, imipenem, ciprofloxacin/levofloxacin, and an aminoglycoside).

 
Among the ß-lactam agents, FQ-R strains exhibited cross-resistance most frequently to ceftazidime (67%), followed by cefepime (62%), imipenem (35%), and least to piperacillin/tazobactam (20%). In contrast, resistance to a ß-lactam agent occurs in 17% or less among FQ-S strains (Figure 2). Strains showing FQ-R were most frequently resistant to gentamicin (58%) followed by tobramycin (48%) and amikacin (23%) whereas less than 10% of FQ-S strains showed resistance to any aminoglycoside (Figure 2).

Outcome analysis

Sixty-five cases and 54 controls were evaluated for outcomes. The following sites of infection were involved: respiratory tract (42%), urinary tract (31%), wound (19%) and blood (2.5%). No significant differences were observed between study groups (data not shown).

Antimicrobial regimen and outcomes

Among those who received an ‘antipseudomonal’ regimen, an FQ agent (primarily levofloxacin) was prescribed in 59% (44/74) of the patients (54% FQ-R versus 64% FQ-S, respectively) (Table 3). When the effectiveness of treatment was evaluated based upon organism susceptibility, only half as many patients in the FQ-R group received effective empirical therapy compared with those in the FQ-S group. Of note, all 19 patients who received an empirical FQ agent in the FQ-R group eventually received an effective antipseudomonal regimen (13/19 were changed to a different agent, 4/19 received combination therapy with at least one antibiotic with activity, whereas addition of an effective agent was seen in 2/19 patients). In addition, receipt of effective therapy was significantly delayed in the FQ-R group compared with controls (Table 3). The overall median duration of therapy was 2 days longer for cases compared with controls; the difference did not reach statistical significance.


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Table 3. Antimicrobial regimens (infected patients)

 
Overall, those infected with FQ-R strains had poorer clinical outcomes compared with controls (Table 4). A significant portion of FQ-R patients only achieved partial response whereas more control patients achieved complete response. In addition, a greater number of patients in the FQ-R group did not achieve clinical stability before discharge and died of sepsis compared with controls. Infection-related mortality was three-fold greater in the FQ-R group compared with controls. Among those who achieved clinical stability, the time required for return of abnormal vital signs and mental status to baseline was prolonged by 5 days in the FQ-R group compared with controls (Figure 3). Among patients infected with FQ-S strains who did not reach clinical stability, two-thirds were discharged alive eventually.


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Table 4. Clinical outcomes (infected patients)

 


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Figure 3. Proportion of patients and time required to achieve clinical stability. FQ-R, fluoroquinolone-resistant (cases); FQ-S, fluoroquinolone-susceptible (controls).

 
By multivariate logistic regression, increasing APACHE II score and underlying pulmonary disease were independently associated with poor treatment response. More importantly, empirical FQ use, FQ-R, and high APACHE II score were identified as independent risk factors for increased mortality (Table 5).


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Table 5. Multivariate analysis on risk factors for poor treatment response and mortality

 

    Discussion
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The recent introduction of newer FQ agents has led to a 78% increase in FQ prescribing in the ambulatory setting between 1992 and 2002.5 In particular, levofloxacin use both in the hospitals and surrounding communities was found to be significantly associated with hospital rates of FQ-R P. aeruginosa; the relationship was not observed with ciprofloxacin use.14 One study noted that as much as half of the levofloxacin prescribed in the emergency department for community-acquired respiratory tract infections was deemed inappropriate based on accepted guidelines.15 Parallel to the increase in prescribing is the rising prevalence of FQ-R P. aeruginosa, with many such strains expressing multidrug resistance. Based on data from the CDC-NNIS system, the prevalence of ciprofloxacin-resistant P. aeruginosa has increased by 37% between 1997 and 2002, which is the greatest increase observed among the top five antibiotic-resistant pathogens (e.g. MRSA, VRE) responsible for nosocomial infections in ICUs.16 Among adults residing in nursing homes, a ciprofloxacin resistance rate approaching 50% in P. aeruginosa isolates was observed in a recent surveillance study carried out in the period 1999–2002.17 Consistent with national trends, our institution experienced a dramatic increase in the prevalence of FQ-R P. aeruginosa from 18% to 54% between 1997 and 2002.

This study examined the risk factors associated with acquisition of FQ-R P. aeruginosa and assessed their impact on outcomes of infection. Our finding of a significant association between FQ use and residence in a long-term care facility with subsequent isolation of FQ-R P. aeruginosa strain is consistent with the findings of others who evaluated this relationship with FQ-R E. coli and K. pneumoniae infections.18 Specifically, FQ use is a significant risk factor that may be modifiable by restricting indiscriminate prescribing.

As observed by others, we demonstrated that many of the FQ-R strains displayed cross-resistance to other antipseudomonal agents.6 MDR phenotype was more likely to be present with FQ-R (12.6 times) and in patients with prior FQ exposure (2.5 times). Over half of our FQ-R strains displayed resistance to an antipseudomonal cephalosporin and an aminoglycoside whereas up to one-third were resistant to imipenem. The strong association between MDR and FQ-R suggests that active drug efflux secondary to an overexpression of efflux pumps is likely involved since these pumps are able to accommodate a wide variety of structurally-unrelated substrates thereby conferring cross-resistance to multiple drug classes.19,20 Indeed, using an efflux pump inhibitor in another study, we have demonstrated that FQ-R strains (which included many of the strains in this study) show a predominance of efflux pump overexpressed phenotype (60% versus 15% of the FQ-R and FQ-S strains, respectively).21 Considering that the FQs are universal substrates for the efflux systems of P. aeruginosa, selection for strains expressing MDR can be expected following FQ exposure.

We have also demonstrated in this study that infections caused by FQ-R P. aeruginosa are significantly associated with adverse outcomes. A lower proportion of patients infected with FQ-R strains achieved a complete response or clinical stability while in hospital compared with those infected with susceptible strains. Among those who achieved clinical stability, the time required to reach stability was significantly prolonged by 5 days in the FQ-R group. More specifically, FQ-R and empirical FQ use were identified to be independent risk factors for increased mortality with P. aeruginosa infections in this study (three- and four-fold increase, respectively). This association may be explained by the delayed administration of effective therapy. Altogether, 75% of FQ-R patients did not receive effective empirical therapy, and a delay of 3.5 days was observed. Because many of our FQ-R strains also displayed the MDR phenotype, the likelihood of effective therapy with any antipseudomonal agent prescribed is lower, further contributing to a delay in effective therapy and adverse consequences.

Several investigators have shown that the effectiveness of empirical therapy is a critical determinant of outcome, and that inadequate antimicrobial therapy is associated with greater infection-related mortality.2224 Similarly, a trend towards higher mortality with increasing length of delay to effective therapy was observed in one study.24 The mean delay in effective therapy was similar to that observed for the FQ-R group in our study (3.5 days).24 Other outcome studies have also noted a correlation between antibiotic resistance (including ciprofloxacin) and unfavourable outcomes (three-fold increase in mortality, nine-fold increase in secondary bacteraemia, and 2.1-fold increase in hospital days).9,11 However, infections caused specifically by P. aeruginosa resistant to FQs and its impact on outcomes have not been previously examined.

We recognize several potential limitations to this study. First, our retrospective study design limits the full assessment of risk factors for acquisition of FQ-R strains and underlying severity of illness. Specifically, details regarding FQ use at an outside hospital or outpatient setting were inconsistently reported, therefore precluding meaningful analysis of the extent of drug exposure on the susceptibility of organism subsequently isolated. We arbitrarily limited our analysis of antibiotic exposure to within 30 days of organism isolation. However, the degree by which drug exposure affects subsequent organism susceptibility may vary depending on the extent and time interval between exposure and first isolation of organism. Prospective culture surveillance studies and detailed reporting of drug exposure are needed to accurately measure the risk of drug exposure and subsequent isolation of resistant organisms.

Secondly, we utilized an APACHE II scoring system to compare the severity of the underlying illness between groups. Since the optimal timing at which the APACHE II score should be calculated is debatable depending upon study end points, we arbitrarily calculated the APACHE II score at the time of hospital admission rather than within 24 h of ICU admission as was done with the original derivation of the scoring system.25 It is possible that the calculated APACHE II score may have underestimated the risk of death for those who were admitted to the ICU for infections caused by study organisms. Nonetheless, we have shown that higher APACHE II score calculated at the time of admission was an independent risk factor predicting non-response and mortality.

Finally, the choice of patients with susceptible organisms as our control group may be associated with selection bias. The risk associated with antibiotic exposure may have been overestimated since patients who received an antibiotic active against the susceptible organisms will inherently make this exposure less frequent among patients who are culture-positive for susceptible organisms than among patients in the source population. However, to quantify the effects of a resistance trait more accurately, in this case FQ-R, a control group consisting of patients infected with a susceptible corresponding strain is considered most appropriate by others.26


    Conclusions
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FQ exposure secondary to widespread prescribing has important implications on the selection for Pseudomonas resistance towards not only FQ agents but to the other antipseudomonal agents in clinical use as well. The gravity of this problem is further compounded by the lack of novel agents with activity against P. aeruginosa in the drug development pipeline.27 At the current rate of increase in the prevalence of FQ-R P. aeruginosa, ciprofloxacin and levofloxacin may no longer be acceptable agents for empirical antipseudomonal therapy, particularly when its use can lead to significant delays in effective therapy and associated adverse outcomes. Based on the results of our study, we urge clinicians to be mindful of the potential collateral damage to Pseudomonas susceptibility and adverse outcomes when an FQ is prescribed as first-line empirical therapy where alternative agents are available. FQ prescribing must be severely limited if we are to slow the rate of development of Pseudomonas resistance and to preserve the utility of existing antipseudomonal agents until the gap in drug development research can be filled.


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Drs Wong-Beringer and Murthy have received grant support and honoraria from speaking engagements and participation in advisory committees from Ortho-McNeil, Wyeth Pharmaceuticals, and Merck Co. Drs Hsu and Okamoto—none declared.


    Acknowledgements
 
No funding has been received for this study. Presented at the 41st Annual Meeting of the Infectious Disease Society of America, San Diego, CA, USA, October 11, 2003 (Poster).


    References
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12 . National Committee for Clinical Laboratory Standards. (2000). Performance Standards for Antimicrobial Disk Susceptibility Tests: M100-S12. NCCLS, Wayne, PA, USA.

13 . Garner, J. S., Jarvis, W. R., Emori, T. G. et al. (1988). CDC definitions for nosocomial infections. American Journal of Infection Control 16, 128–40.[ISI][Medline]

14 . Polk, R. E., Johnson, C. K., McClish, D. et al. (2004). Predicting hospital rates of fluoroquinolone-resistant Pseudomonas aeruginosa from fluoroquinolone use in US hospitals and their surrounding communities. Clinical Infectious Diseases 39, 497–503.[CrossRef][ISI][Medline]

15 . Malcolm, C. & Marrie, T. J. (2003). Antibiotic therapy for ambulatory patients with community-acquired pneumonia in an emergency department setting. Archives of Internal Medicine 163, 797–802.[Abstract/Free Full Text]

16 . National Nosocomial Infections Surveillance (NNIS). (2003). National Nosocomial Infections Surveillance (NNIS) System Report, data summary from January 1992 to June 2003, issued August 2003. American Journal of Infection Control 31, 481–98.[CrossRef][ISI][Medline]

17 . Flamm, R. K., Weaver, M. K., Thornsberry, C. et al. (2004). Factors associated with relative rates of antibiotic resistance in Pseudomonas aeruginosa isolates tested in clinical laboratories in the United States from 1999–2002. Antimicrobial Agents and Chemotherapy 48, 2431–6.[Abstract/Free Full Text]

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21 . Kriengkauykiat, J., Porter, E., Lomovskaya, O. et al. (2005). Use of an efflux pump inhibitor to determine efflux pump mediated fluoroquinolone resistance in Pseudomonas aeruginosa. Antimicrobial Agents and Chemotherapy 49, 565–70.[Abstract/Free Full Text]

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