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Fluoroquinolone Resistance in Escherichia Coli Isolates After Exposure to Non-fluoroquinolone Antibiotics: a Retrospective Case–Control Study

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Fluoroquinolone Resistance in Escherichia Coli Isolates After Exposure to Non-fluoroquinolone Antibiotics: a Retrospective Case–Control Study J Antimicrob Chemother 2020; 75: 1985–1992 doi:10.1093/jac/dkaa128 Advance Access publication 12 May 2020 Fluoroquinolone resistance in Escherichia coli isolates after exposure to non-fluoroquinolone antibiotics: a retrospective case–control study Linda E. Chaname Pinedo 1*, Robin Bruyndonckx2,3, Boudewijn Catry4,5, Katrien Latour4, Herman Goossens3, Steven Abrams1,2 and Samuel Coenen 1,3,6 1Department of Epidemiology and Social Medicine, University of Antwerp, Antwerp, Belgium; 2Interuniversity Institute for Biostatistics Downloaded from https://academic.oup.com/jac/article/75/7/1985/5836063 by vdic user on 05 January 2021 and statistical Bioinformatics, Data Science Institute, Hasselt University, Diepenbeek, Belgium; 3Laboratory of Medical Microbiology, Vaccine & Infectious Disease Institute, University of Antwerp, Antwerp, Belgium; 4Healthcare-Associated Infections and Antimicrobial Resistance Unit, Scientific Directorate of Epidemiology and Public Health, Sciensano, Brussels, Belgium; 5Faculty of Medicine, Universite´ libre de Bruxelles, Brussels, Belgium; 6Department of Primary and Interdisciplinary Care, University of Antwerp, Antwerp, Belgium *Corresponding author. Present address: Faculty of Microbiology, Cayetano Heredia University, Lima, Peru. E-mail: [email protected] Received 29 November 2019; returned 24 December 2019; revised 6 March 2020; accepted 11 March 2020 Objectives: To investigate whether prior exposure to non-fluoroquinolone antibiotics increases the risk of fluoro- quinolone resistance in Escherichia coli. Methods: This was a secondary analysis of data collected retrospectively in a case–control study linking micro- biological test results (isolated bacteria and their susceptibility) of urine samples routinely collected from pri- mary, secondary and tertiary care patients in Belgium with information on prior antibiotic use at the patient level up to 1 year previously. Results: In urine samples from 6125 patients, 7204 E. coli isolates were retrieved [1949 fluoroquinolone- resistant isolates (cases) and 5255 fluoroquinolone-susceptible isolates (controls)]. After adjusting for potential confounders (including fluoroquinolone use) and correcting for multiple testing there were lower odds of fluoro- quinolone resistance in E. coli isolates after exposure to cefazolin (OR = 0.65; 95% CI = 0.52–0.81; P = 0.00014) and higher odds after exposure to trimethoprim/sulfamethoxazole (OR = 1.56; 95% CI = 1.23–1.97; P =0.00020) or nitrofurantoin (OR = 1.50; 95% CI = 1.23–1.84; P =0.000083). A sensitivity analysis excluding samples with anti- biotic use during the 6 months prior to the sampling date confirmed the higher odds of fluoroquinolone resist- ance after exposure to trimethoprim/sulfamethoxazole and nitrofurantoin. Conclusions: Assuming no residual confounding or other biases, this study suggests that exposure to non- fluoroquinolone antibiotics, i.e. trimethoprim/sulfamethoxazole and nitrofurantoin, might be causally related to fluoroquinolone resistance in E. coli isolates from urinary samples. Future prospective research is needed to con- firm non-fluoroquinolone antibiotics as potential drivers of fluoroquinolone resistance. Introduction Pseudomonas aeruginosa and E. coli found older age,4 residency in long-term care facilities,5 recent hospitalization,9 the use of a Fluoroquinolones, a major class of antibiotics, belong to the WHO 7 list of highest priority antimicrobials for resistance surveillance in urinary catheter and previous exposure to non-fluoroquinolone 5,10,12–14 human medicine.1 In various European countries, considerable antibiotics as independent risk factors for fluoroquinolone increases in ciprofloxacin resistance in Escherichia coli causing un- resistance. The link between non-fluoroquinolones and fluoro- complicated urinary tract infections were found between 2000 quinolone resistance can be explained by the phenomenon of 15,16 and 2014.2 Although a slight decrease in fluoroquinolone resist- co-selection. ance was reported in Belgium, from 26.7% in 2014 to 23.8% in Even though investigators have identified several non- 2017, it was still high compared with other northern European fluoroquinolone antibiotics as independent risk factors for fluoro- countries, such as the Netherlands (14.2% in 2017) and Denmark quinolone resistance,4,5,12–14,17 most of these studies had no infor- (12.8% in 2017).3 mation on prior antibiotic use (i.e. before hospitalization), only While fluoroquinolone use is likely the main driver of resistance included hospitalized patients, had small sample sizes and, in to fluoroquinolones,4–11 we need to consider other risk factors. some case–control studies, controls were taken from the same Previous studies on Enterococcus species, Klebsiella pneumoniae, hospital, with a high probability of selection bias and resulting VC The Author(s) 2020. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For permissions, please email: [email protected]. 1985 Chaname Pinedo et al. in a persistent effect of a previous selection pressure of an mainly done by the Kirby–Bauer disc diffusion technique according to CLSI antimicrobial. guidelines. Modifications were present according to the manufacturer for Identification of a causal relationship between non- deviations in disc charge or diameter. The majority of Belgian hospitals 20 fluoroquinolone antibiotic use and fluoroquinolone resistance worked with Neo-Sensitabs for producing these antibiograms. could guide treatment options to reduce fluoroquinolone resist- ance and enhance our understanding of co-selection. Therefore, Covariates we investigated the increased risk of fluoroquinolone resistance We considered potential confounders to be any variable suspected to be in urinary E. coli samples collected from primary, secondary and linked to both fluoroquinolone resistance and non-fluoroquinolone anti- tertiary healthcare settings in Belgium by the use of non- biotic use. Confounding variables were extracted from the antibiotic use fluoroquinolone antibiotics in the year prior to the sampling date. and sociodemographic data and included prior or current use of fluoroqui- We hypothesized that we would find associations between non- nolones (yes/no), whether the urine sample was taken in a hospital (yes/ Downloaded from https://academic.oup.com/jac/article/75/7/1985/5836063 by vdic user on 05 January 2021 fluoroquinolone antibiotic use and fluoroquinolone resistance. no), the total number of days that a patient stayed in the hospital during Additionally, we assessed effect modification of this relationship the 6 months before the urine sample was taken (zero if the patient was not hospitalized in the last 6 months), the most recent time between any by exposure to fluoroquinolones. antibiotic use and a susceptibility test for fluoroquinolones (in days), age (in years), gender (female/male) and any other antibiotic use. We also Methods assessed modification of the relationship between non-fluoroquinolones and fluoroquinolone resistance by fluoroquinolone use for the secondary Study design and setting aim of the study. We performed a secondary analysis of data collected retrospectively from primary, secondary and tertiary care patients in Belgium during a case–con- Statistical methods trol study. Microbiological test results (1 January 2011 to 31 December Categorical variables were described using proportions, while continuous 2012) were linked with data on prior antibiotic use at the patient level (1 variables were summarized using medians and IQRs. Significance of differ- January 2010 until 31 December 2012) up to 1 year before sample collec- 18 ences in median values (for continuous variables) or proportions (for tion and susceptibility testing for fluoroquinolones. More information on categorical variables) among cases and controls were assessed using a the data sources, linkage, data access and cleaning methods is available as Wilcoxon rank sum test or Fisher’s exact test, respectively. The (2%2) con- Supplementary data S1 at JAC Online. tingency table analyses included only antibiotics with a least 5 counts per cell. Study population To quantify the relationship between fluoroquinolone resistance and In the linked dataset, including 197 393 urine samples, E. coli was isolated the use of each of the non-fluoroquinolone antibiotics (both alone and as a from 21 569 (10.9%) samples. Ciprofloxacin susceptibility was tested for group), a generalized estimating equation (GEE) approach for a binary out- 16 593 (76.9%) of these E. coli strains and for 1743 (10.5%), 106 (0.6%), come was used to accommodate dependence in observations related to 21 3415 (20.6%) and 11 329 (68.3%) the test result was unknown, intermedi- the same individual, thereby producing crude ORs with their 95% CIs. ate, resistant and susceptible, respectively. After selecting only antibiotic In model 1, a multivariable GEE approach was used to adjust for con- use up to 1 year prior to sample testing, we obtained a total of 8400 sam- founding variables. Since multicollinearity was not an issue when adding all ples. From this data, we excluded samples from the same patient within covariates in an initial full model [to check for multicollinearity we used 30 days as this cut-off point is often used to differentiate between the (generalized) variance inflation factors, calculated using the car package in same and a new urinary tract infection episode,16 resulting in a total of R, which had values <4], and our sample size was large
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