1 Center for Health Equity Research and Promotion, Philadelphia Veterans Affairs Medical Center; 2 Departments of Medicine and Biostatistics and Epidemiology, the Center for Clinical Epidemiology and Biostatistics, the Center for Education and Research on Therapeutics, and the Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA
Received 11 October 2001; returned 21 May 2002; revised 21 October 2002; accepted 27 December 2002
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Abstract |
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Materials and methods: This was a retrospective casecontrol study. Subjects were veterans with Gram-negative UTIs seen at the Philadelphia VA Medical Center from 1 July 1996 to 31 December 1999. Subjects were linked to a national VA outpatient pharmacy database. Cases and controls were identified based on the results of trimethoprimsulfamethoxazole susceptibility testing.
Results: Three hundred and ninety-three veterans with UTIs could be linked to electronic pharmacy records. The overall rate of trimethoprimsulfamethoxazole drug resistance was 13%, without significant annual variation. Antimicrobial drug exposure within 6 months was strongly associated with the probability of a trimethoprimsulfamethoxazole-resistant infection (OR = 4.1, 95% CI 2.27.5). This association extended to exposure to other antimicrobial drugs in addition to trimethoprimsulfamethoxazole and the overall association displayed a doseresponse relationship in terms of the number of prior drug exposures.
Conclusions: Prior antimicrobial drug exposure is a strong risk factor for infection with trimethoprimsulfamethoxazole-resistant Gram-negative bacteria among patients with UTIs.
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Introduction |
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It seems likely that this rising resistance is due to Darwinian selection resulting from widespread use of antibiotics. However, evidence for this causal relationship in community settings is limited and includes ecological (i.e. population level) studies, comparing community level rates of resistance with rates of antibiotic consumption,69 and carriage studies, examining the causal association between antibiotic exposure and carriage of, not infection with, resistant bacteria.10,11 Moreover, if antibiotic exposure is causal, then exposure should demonstrate a clear doseresponse relationship with the subsequent risk of a drug-resistant infection rising as the number of courses of antibiotics increases.12 There is a growing awareness that not all antimicrobial drugs and patterns of antimicrobial drug use are equivalent in terms of their propensity to select for drug-resistant bacteria.13 However, data on these relationships have been limited by the difficulties in accurately measuring antimicrobial drug exposures through traditional methods of patient self-report or medical record review.
Recently, the Department of Veterans Affairs established a national formulary and began maintaining centralized records of all pharmacy dispensings throughout the Veterans Health Administration. Such a database, if linked to laboratory data capturing drug-resistant and -susceptible infections, could provide valuable details on the risk factors for drug-resistant infections. We chose to study veterans with trimethoprimsulfamethoxazole-resistant Gram-negative urinary tract infections (UTIs) because these are common infections with a clinically relevant level of resistance to a first-line antimicrobial therapy. The specific aim of this study was to identify patterns of antimicrobial drug exposure associated with infection with trimethoprimsulfamethoxazole-resistant Gram-negative pathogens in veterans with UTIs.
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Materials and methods |
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We conducted a retrospective casecontrol study using linked local laboratory and national pharmaceutical electronic records within the VA Healthcare System. The study was based at the ambulatory care clinics within the VA Medical Center, Philadelphia, PA from 1 July 1996 to 31 December 1999. The specific locations included were any of the outpatient primary care clinic sites (including separate geriatric and womens health clinics), the emergency department and the outpatient urology clinic. We identified the location of potential subjects based on the coded source of submission for all urine cultures submitted to the hospital laboratory during the study period.
Potential study subjects were all subjects with growth from a urine specimen of 5 x 104 cfu/mL of either a single Gram-negative bacterium or a dominant bacterium (i.e.
5 x 104 cfu/mL of one pathogen and
103 cfu/mL of a second pathogen). The cutpoint for significant growth was chosen because this was the lowest density of growth that consistently underwent susceptibility testing during the study period. Others have demonstrated that as low as 104 cfu/mL of a single uropathogen is a sensitive and specific indicator of UTIs in men.14,15
Urine cultures
All data for this study were obtained through existing electronic databases within the VA Healthcare System. Laboratory data are housed at local VA facilities in a decentralized data structure called Veterans Information Systems Technology Architecture (VISTA).16 We captured all positive urine cultures for the study period, including date of infection, hospital location for test submission and results of urine culture, including all susceptibility testing.
All potentially eligible urine cultures were analysed during the period 1 July 1996 to 31 December 1999. For those subjects with more than one positive culture during the study period, we included only the initial positive culture during the 3.5 year study window. Susceptibility results were collected based on the clinical laboratory report of the results of in vitro trimethoprimsulfamethoxazole susceptibility testing. Susceptibility testing was carried out with an automated rapid susceptibility testing instrument, VITEK (bioMérieux), with resistance to trimethoprimsulfamethoxazole defined at 4 mg/L trimethoprim and
76 mg/L sulfamethoxazole.
Antibiotic exposure
Drug exposure data were extracted from the Pharmacy Benefits Management (PBM) database, maintained by the PBM Strategic Health Care Group at Hines Hospital, IL, USA. Since 1999, this national pharmacy database has extracted outpatient and inpatient drug dispensing data from each VA medical facility. We were able to expand the local Philadelphia PBM data back to 1 January 1996 using archived electronic pharmacy dispensing data at the local facility, thus providing at least 6 months of pharmacy data preceding the most recent infections in our study.
For the initial Gram-negative UTI for each patient identified within the 3.5 year laboratory database, we linked to the PBM data for the 6 months preceding the date of culture. Antimicrobial drug exposures preceding the UTI were identified based on the VA pharmacy codes of the dispensed drugs. The VA drug class code is a five-digit code that captures the category and class of drug dispensed. We captured all outpatient dispensings in order to categorize antimicrobial drugs as well as other drugs that might be indicators of chronic conditions. We excluded antimicrobial drugs prescribed within 14 days of the index urine culture in order to avoid the potential for misclassification of a treatment as a preceding exposure. For patients who received antimicrobial drugs during the 6 month window preceding infection, we recorded the drug class and cumulative number of separate prescriptions for antimicrobial drugs.
The pharmacy database provided a limited opportunity to examine the potential role of other factors as determinants of trimethoprimsulfamethoxazole-resistant UTIs. We selected factors based on their prior identification as potential risk factors as well as the accuracy of the pharmacy database to identify these conditions.17 The two factors included in this study were the presence of pharmacologically treated diabetes mellitus (VA pharmacy codes for insulin or oral hypoglycaemic agents) and the chronic use of an indwelling catheter (VA pharmacy codes for Foley catheters or urine collection devices).
Analysis
Descriptive statistics were used to present the distributions of Gram-negative bacterial pathogens, susceptibility results and antimicrobial drug exposures among study subjects. Bivariate associations between the presence of antimicrobial drug exposures or other potential risk factors and the subsequent antimicrobial susceptibility of the uropathogen were analysed using 2 or Fishers exact statistics as appropriate.18 The impact of number of courses of antimicrobial exposure on susceptibility was tested with the MantelHaenszel
2 test for trend,19 excluding those subjects without prior antimicrobial drug exposure since they do not contribute information to the doseresponse analysis. Stratified analyses were conducted to examine the impact of site care on the relationship between antimicrobial drug exposure and the probability of a trimethoprimsulfamethoxazole-resistant infection. The BreslowDay test statistic was used to assess the homogeneity of odds ratios across the site strata.20 Multivariable logistic regression was used to assess the independent association between prior antimicrobial drug exposure and the probability of a trimethoprimsulfamethoxazole-resistant infection, controlling for patient age, site of care, Foley catheter use and the presence of treated diabetes mellitus. A separate logistic regression was used to assess the independent association between each class of antimicrobial drug exposure and the probability of a trimethoprimsulfamethoxazole-resistant infection, simultaneously controlling for all other classes of antimicrobial drug exposure. All analyses were conducted with SAS for Unix (Release 6.12; SAS Institute, Cary, NC, USA).
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Results |
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Table 1 reports the characteristics of these patients and their infections; 53% of the study subjects were 65 years at the time of their UTI. Based on pharmacy dispensing records, 25% of subjects had diabetes mellitus and 9% of subjects required intermittent or chronic bladder catheterization; 33% of the subjects had received at least one antimicrobial drug in the 6 month window of time preceding the UTI, and this rate of exposure did not vary significantly over the study years. The most commonly prescribed antimicrobial drugs for this study population included trimethoprimsulfamethoxazole (40% of all antimicrobial drugs prescribed), quinolones (32%) and penicillins (23%). The proportion of antimicrobial drug prescriptions accounted for by trimethoprimsulfamethoxazole declined over the study period from a high of 70% to a low of 23% (P = 0.007 for trend), whereas the other major drug classes remained relatively constant.
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Table 2 compares the antibiotic exposure frequencies of patients with trimethoprimsulfamethoxazole-susceptible and -resistant UTIs. Prior exposure to any antimicrobial drug was found among 61% of patients with trimethoprimsulfamethoxazole-resistant UTIs compared with 27% of those with trimethoprimsulfamethoxazole-susceptible UTIs (OR = 4.1, 95% CI 2.27.5). Patient age, presence of treated diabetes mellitus and chronic use of Foley catheters were not significantly associated with the probability of a trimethoprimsulfamethoxazole-resistant infection. In analyses stratified by the site of care, the relationship between prior antimicrobial drug exposure and infection with a trimethoprimsulfamethoxazole-resistant uropathogen demonstrated significant heterogeneity (P = 0.03 by BreslowDay test), but when the urology site of care was excluded from the analysis, the relationship between prior antimicrobial drug exposure and infection with a trimethoprimsulfamethoxazole-resistant uropathogen was homogeneous across the remaining site of care strata (P = 0.17). In multivariable logistic regression analysis, the association between prior antimicrobial drug exposure and infection with a trimethoprimsulfamethoxazole-resistant uropathogen remained essentially unchanged after adjusting for age, site of care, treated diabetes mellitus and Foley catheter use (OR = 4.4, 95% CI 2.38.5 with urology sites included; OR = 5.3, 95% CI 2.710.5 with urology sites excluded).
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Figure 1 shows a strong relationship between the number of antibiotic courses received in the preceding 6 months and the likelihood of a trimethoprimsulfamethoxazole-resistant UTI. The proportion of resistant isolates ranged from as low as 8% for those without prior antimicrobial prescriptions to as high as 39% for those with three or more prior prescriptions (P = 0.01 for a doseresponse trend for increasing numbers of prior drug prescriptions excluding patients with no prior antibiotic exposures).
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Discussion |
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Prior antimicrobial drug exposure has been identified as a key risk factor for drug-resistant UTIs,2126 but, as with other antibiotic-resistant infections, the doseresponse nature of this relationship has not previously been described. Mathematical models predict that, on a population level, once a threshold is reached, the prevalence of resistant bacteria will rise steeply as antibiotic exposure increases.27 By linking laboratory data to a comprehensive pharmacy dispensing database, we were able to demonstrate a direct doseresponse relationship between individual exposure to antimicrobial drugs and subsequent individual infection with drug-resistant pathogens, strongly supporting the causal nature of this relationship. Based on Hills criteria for causality, evidence to date in support of this causal relationship includes strength of association, consistency, specificity, temporality, plausibility, coherence and evidence for a biological gradient. The primary remaining criterion, experimental evidence of causality, awaits further results from efforts under way to reduce antibiotic exposure in communities as a means to reduce antibiotic resistance.6
Other factors have been implicated as potential risk factors for trimethoprimsulfamethoxazole-resistant UTIs, including diabetes mellitus, urinary tract anomalies, prior hospitalization and prior exposure to oestrogens.22,24,26 However, most of these factors have not been validated as independent risk factors after controlling for prior antimicrobial drug exposure. Our study had limited information on these other potential risk factors and the number of subjects exposed to these risk factors was small, but, based on pharmaceutical indicators, we found no relationship between pharmacologically treated diabetes mellitus or chronic urinary tract catheterization and the risk of a trimethoprimsulfamethoxazole-resistant infection.
Another issue in understanding the relationship between drug exposure and drug-resistant infections reflects the fact that the strongest promoters of specific patterns of resistance are not necessarily the drugs to which the pathogen demonstrates resistance. In this study, trimethoprimsulfamethoxazole exposure was strongly associated with trimethoprimsulfamethoxazole resistance, but exposures to quinolones and tetracyclines were also strongly associated with trimethoprimsulfamethoxazole resistance. Patterns of selection of drug-resistant strains that cross therapeutic drug classes have been reported previously,9,28,29 and would be expected in the setting of multidrug resistance, particularly with the multidrug-resistant plasmids that are present in enterobacteria. Alternatively, as predicted by mathematical models, any antimicrobial drugs that reduce the risk of colonization with susceptible bacteria may increase the probability that a host will be subsequently colonized by specific drug-resistant pathogens as the proportion of specific drug-resistant pathogens in the environment increases.30
An alternative interpretation of our results is that prior antimicrobial drug prescriptions are a marker of prior resistant UTIs rather than a cause of subsequent resistant UTIs. To the extent that providers do not always send cultures before treating infections, some prior UTIs may have been missed due to our reliance on the laboratory database to identify all infections. However, we specifically excluded antimicrobial drug prescriptions within 14 days of the positive urine culture in order to minimize this misclassification and analysed only the first culture documented UTI for each subject.
Several limitations of this study should be noted. First, data on antimicrobial drug exposure were limited to information included within the outpatient pharmacy dispensing files of the VA. Thus, antimicrobial drugs dispensed by non-VA pharmacies would not be measured in our study. In a separate study, we have shown that 17% of a random sample of veterans self-report antimicrobial drug prescriptions from non-VA providers over a 6 month period (J. P. Metlay, unpublished observations). Assuming that this under-measurement of exposure was non-differential with respect to the susceptibility of the infection, this bias should have reduced the magnitude of the association measured. Moreover, 30% of the eligible subjects identified in the microbiology laboratory database could not be linked to the pharmacy database, reflecting errors in the coding of patient identifiers as well as the fact that some patients seen at the VA did not have dispensed medications during the 6 month period preceding the time of their infection.
Secondly, we had limited information on other risk factors beyond prior antimicrobial drug exposure. In particular, we focused on UTIs identified in ambulatory care sites but we did not have information on prior hospitalizations. Thus, some of the pathogens may have been hospital acquired. Moreover, the heterogeneous nature of the patient population probably resulted in differential thresholds for submitting urine cultures in the face of a suspected UTI, which may have confounded the relationship between prior drug exposure and subsequent risk of a resistant UTI. Indeed, our analysis revealed that the observed relationship between prior drug exposure and subsequent risk of a resistant UTI was not homogeneous across the different sites of care. However, this heterogeneity was primarily driven by data from the urology site, and the overall relationship between prior drug exposure and risk of a resistant UTI was similar whether data from this site were included or excluded from the analysis. Finally, beyond our simple measures of site of care, treated diabetes mellitus and use of Foley catheters, we had limited data on the severity of illness and complicated nature of the UTIs and were, therefore, unable to control for these factors in our analysis.
Thirdly, our casecontrol study relied on controls selected among subjects with drug-susceptible UTIs. However, the true source population of our cases includes all subjects who could potentially seek care at the VA for a UTI. Controls selected based on their infection with a susceptible isolate may provide an underestimate of the antimicrobial drug exposure rate in the source population, thus overestimating the magnitude of the association between antimicrobial drug exposures and drug-resistant infections.31 However, limited empirical data indicate that, in comparison with random controls from the source population, controls selected based on isolation of susceptible isolates actually provide lower measures of associations between drug exposure and drug-resistant infections.22 Furthermore, our own data indicate that antimicrobial drug exposure rates are higher among the control groups used in this study compared with subjects selected randomly from the VA primary care enrolment files (data not shown).
Finally, this study focused on patients at a single clinical site, examined only Gram-negative uropathogens, and resistance only to a single agent, trimethoprimsulfamethoxazole. We did not observe sufficient numbers of Gram-positive UTIs to include in this analysis, and rates of resistance to other agents, particularly fluoroquinolones, were too low for analysis. Whereas the patterns of association observed in this study may be generalizable to other pathogens and other resistance patterns, future studies examining each of these conditions will need to consider the potential uniqueness of these associations.
In conclusion, prior antimicrobial drug exposure is a strong risk factor for infection with a drug-resistant Gram-negative uropathogen. The association demonstrates a steep doseresponse relationship in terms of the number of prior courses of antimicrobial drugs. Understanding the complex relationship between patterns of drug exposure and emerging drug resistance should inform future guidelines for antimicrobial drug therapy. Future studies must establish whether these patterns of association will be consistent across diverse clinical settings and different patterns of drug resistance.
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Acknowledgements |
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This paper was presented in part at the national meeting of the Infectious Diseases Society of America, New Orleans, LA, USA, 2000.
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Footnotes |
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