Increased fluoroquinolone resistance with time in Escherichia coli from >17,000 patients at a large county hospital as a function of culture site, age, sex, and location
© Boyd et al; licensee BioMed Central Ltd. 2008
Received: 02 October 2007
Accepted: 15 January 2008
Published: 15 January 2008
Escherichia coli infections are common and often treated with fluoroquinolones. Fluoroquinolone resistance is of worldwide importance and is monitored by national and international surveillance networks. In this study, we analyzed the effects of time, culture site, and patient age, sex, and location on fluoroquinolone resistance in E. coli clinical isolates.
To understand how patient factors and time influenced fluoroquinolone resistance and to determine how well data from surveillance networks predict trends at Ben Taub General Hospital in Houston, TX, we used Perl to parse and MySQL to house data from antibiograms (n ≅ 21,000) for E. coli isolated between 1999 to 2004 using Chi Square, Bonferroni, and Multiple Linear Regression methods.
Fluoroquinolone resistance (i) increased with time; (ii) exceeded national averages by 2- to 4-fold; (iii) was higher in males than females, largely because of urinary isolates from male outpatients; (iv) increased with patient age; (v) was 3% in pediatric patients; (vi) was higher in hospitalized patients than outpatients; (vii) was higher in sputum samples, particularly from inpatients, than all other culture sites, including blood and urine, regardless of patient location; and (viii) was lowest in genital isolates than all other culture sites. Additionally, the data suggest that, with regard to susceptibility or resistance by the Dade Behring MicroScan system, a single fluoroquinolone suffices as a "surrogate marker" for all of the fluoroquinolone tested.
Large surveillance programs often did not predict E. coli fluoroquinolone resistance trends at a large, urban hospital with a largely indigent, ethnically diverse patient population or its affiliated community clinics.
E. coli is the most common etiologic agent of infections caused by Gram-negative bacilli, and these infections routinely are treated with fluoroquinolones, some of the most-frequently prescribed antibiotic classes . National and international surveillance networks track the frequency of susceptibility to antimicrobial agents, including the fluoroquinolones. Some fluoroquinolone data, such as that showing that males are more likely than females to have resistant isolates, reveal clear trends [2–4]. Other data from these networks can vary. For example, one study uncovered that younger patient age was associated with increased likelihood of having a ciprofloxacin non-susceptible isolate , but another report of urinary E. coli isolates found that resistance was highest in patients ≥ 65 years of age . Low numbers of isolates from each participating hospital, variations in patient populations, and differences in geographical regions of these hospitals may play a role in the variation in the data. Large-scale, local studies, therefore, are required to understand drug resistance in a given community.
We analyzed the effects of patient factors on fluoroquinolone resistance over time at Ben Taub General Hospital, a 578 bed, acute-care, county hospital that serves a mostly Hispanic and African-American patient population in Houston, Texas. The hospital microbiology laboratory also provides service to twelve community health centers across Harris County, Texas. This retrospective study differs from surveillance network studies in that data from thousands of E. coli isolates from a single hospital laboratory were analyzed simultaneously. Antibiotic susceptibilities were determined using the Dade Behring MicroScan system (Sacramento, CA, USA) according to Clinical Laboratory Standards Institute (CLSI) guidelines . Data from all E. coli antibiograms from July 1, 1999 to December 31, 2004 (n ≅ 21,000) were parsed with Perl and imported into a MySQL database (Uppsala, Sweden). All database queries only included information from the first isolate for each patient (n ≅ 17,000). Female patients outnumbered males 3.5 to 1, with age ranging from 0.01 to 103 years (average females = 39.5 ± 20.6, males = 41.9 ± 24.9). Ciprofloxacin, gatifloxacin, levofloxacin, norfloxacin, and ofloxacin were included among the ~25 different antibiotics in the antibiograms, although gatifloxacin has since lost approval for systemic, but not ophthalmic, use. Chi square analysis and the Bonferroni correction were used to analyze all the data, and P ≤ 0.01 (99% confidence interval) was required for statistical significance. We also determined the odds ratio of resistance to susceptibility with a multiple logistic regression equation using SPSS (Chicago, IL, USA).
Results and Discussion
Fluoroquinolone resistance increased with time
It has been thought that fluoroquinolones exemplify a "class effect," such that when resistance mechanisms decrease susceptibility for one drug, they do so simultaneously for all . Each mechanism, however, affects different fluoroquinolones to varying extents , and some mechanisms, such as Aac(6')-Ib-cr  and QepA , decrease susceptibility only to ciprofloxacin and norfloxacin. Thus, it was important to distinguish whether time or specific fluoroquinolone accounted for the resistance differences shown in Fig. 1A. Comparing fluoroquinolones for a single year (2002), in which ciprofloxacin, gatifloxacin, and levofloxacin were all tested routinely, revealed that the frequency of resistance for the three fluoroquinolones was statistically indistinguishable, ~15% (Fig. 1C). An independent test of whether there were any variations among the fluoroquinolones was to look for isolates that were "I" or "R" to one drug and "S" to another. When ciprofloxacin and gatifloxacin (n = 6,272), levofloxacin and ciprofloxacin (n = 560), or levofloxacin and gatifloxacin (n = 582) were analyzed, 1–4% of isolates were non-susceptible to one drug and susceptible to the other. The small number of differentially susceptible isolates were equally likely to be non-susceptible to one drug while susceptible to another, and these few measurement differences likely represent the Dade MicroScan error rate .
To test whether time or specific fluoroquinolone accounted for the differences in Fig. 1A, we measured fluoroquinolone MICs by the agar dilution method independently in our laboratory . We quantified MICs in 242 representative isolates from Ben Taub that were collected over the duration of this study. When ciprofloxacin, gatifloxacin, levofloxacin, and norfloxacin MICs were compared, all isolates that had non-susceptible MICs to one fluoroquinolone had non-susceptible MICs for all four drugs. Thus, what initially appeared to be drug differences in Fig. 1A were, in fact, a consequence of which drugs were tested over time. Our data and others  suggest that the susceptibility status of at least ciprofloxacin, gatifloxacin, levofloxacin, and norfloxacin could be inferred from testing only one of these drugs as a "surrogate marker." Because of these data, we conclude that fluoroquinolones indeed exhibit a class effect with regard to susceptibility as measured by the Dade Behring MicroScan system, and we combine data for all fluoroquinolones in subsequent analyses.
Variation in resistance in the hospital and at outpatient community clinics
Unlike most antibiotics in the United States, ciprofloxacin resistance has not been reported to be higher in isolates from patients in the ICU than in inpatients and outpatients [3, 4, 15]. In our population, however, resistance (~19% of >4,000 patients) in ICU and inpatient isolates (statistically indistinguishable from each other) occurred more frequently than in outpatients (~9% of >12,500 patients, P < 0.0001; data not shown). Hospital outpatients were significantly more likely (P < 0.001) to have a resistant isolate (11%) than outpatients who received care from the twelve community health centers (~8%). Resistance at most community clinics was statistically indistinguishable from community outpatients as a whole, except for two clinics with significantly higher resistance (~14%, P < 0.01) and two other clinics where resistance was significantly lower (~3%, P < 0.001). Outpatient community health centers serviced by the hospital microbiology laboratory provided care to all patients seeking treatment, with the exception of the clinic with the highest prevalence of resistance, which provides care for HIV-positive patients. Unlike the HIV clinic, patients at all other clinics did not have any known specific illness. These data show that the majority of outpatients had the same likelihood of having a resistant isolate, regardless of whether they received care in the community or at the hospital.
Fluoroquinolone resistance as a function of culture site
Isolate culture sites as a function of susceptibility status
Number of isolates
Fluoroquinolone resistance as a function of patient age
Approximately 2% of ≤ 10 year-old children had fluoroquinolone-resistant E. coli isolates. These children should have been naïve to fluoroquinolones, as the use of these antibiotics in pediatric patients generally is not recommended. To ascertain whether these children presented with the infections around the same time, which could indicate an outbreak or clonal spread, we determined when and where they had been treated. The majority of children with resistant isolates were outpatients, but no obvious temporal association was detected. Although the only licensed use of fluoroquinolones in children is treatment of post-inhalation anthrax exposure with ciprofloxacin, some compassionate use occurs in children suffering from serious infections, such as multidrug resistant infections . In Houston, children with serious illness generally would be treated at Texas Children's Hospital, not Ben Taub General Hospital. Thus, most pediatric patients at Ben Taub, just as in the United States as a whole, should not have had prior fluoroquinolone exposure. Although our data did not control for previous antibiotic therapy, two previous studies that did also found that ~2% of children harbored quinolone- or fluoroquinolone-resistant isolates [19, 20]. Therefore, a small percentage of children may carry fluoroquinolone-resistant E. coli independently of prior fluoroquinolone use. The affected children may have acquired the fluoroquinolone-resistant isolates from a family member or in the community, although outbreaks of gram-negative bacteria are rarely reported . However, because such surveillance efforts currently monitor the spread of virulent bacteria like E. coli O157:H7, less virulent strains that do not cause significant morbidity might be passed undetected from person to person.
Increased resistance in urinary isolates from male outpatients
Fluoroquinolone resistance patterns are complicated, making it difficult to apply national data to clinical practice in any specific area. Studies that identify resistance trends on a local or regional scale ([30, 31], this study) are more directly applicable to a given area and could help better guide prescribing practices of clinicians. In addition, it is important to disseminate such regional data, as they might be harbingers of trends that may spread to or be encountered in other regions in the future. This is particularly true for the fluoroquinolones, because their prescribing increased sharply since the 1990s in the United States  and likely in other countries worldwide as well. Finally, meta-analyses of regional studies might explain the variations in resistance trends from international surveillance networks and even predict such trends not only for E. coli, but also for other bacterial species, given the high conservation of the fluoroquinolone target topoisomerases across divergent species.
We thank Barbara E. Murray, M.D.; Timothy G. Palzkill, Ph.D.; Joseph F. Petrosino, Ph.D.; Charles E. Stager, Ph.D.; and James Versalovic, M.D. Ph.D., for advice and Christopher H. Boyd; Daniel J. Catanese, Jr., Ph.D.; and Robert M. Ward for technical assistance. This work was funded by NIH Grant RO1 AI054830 (ELZ), by the Pharmacoinformatics (NIH Grant T90 DK070109; LSB) and the Computational Biology and Medicine (NLM Grant T15 LM07093; GLR) Training Programs of the W. M. Keck Center for Computational and Structural Biology of the Gulf Coast Consortia, and in part by the Department of Veterans Affairs (RJH).
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