Characteristics of the antibiotic regimen that affect antimicrobial resistance in urinary pathogens

Abstract Background Treatment duration, treatment interval, formulation and type of antimicrobial (antibiotic) are modifiable factors that will influence antimicrobial selection pressure. Currently, the impact of the route of administration on the occurrence of resistance in humans is unclear. Metho...

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Bibliographic Details
Main Authors: Boudewijn Catry, Katrien Latour, Robin Bruyndonckx, Camellia Diba, Candida Geerdens, Samuel Coenen
Format: Article
Language:English
Published: BMC 2018-06-01
Series:Antimicrobial Resistance and Infection Control
Subjects:
Online Access:http://link.springer.com/article/10.1186/s13756-018-0368-3
Description
Summary:Abstract Background Treatment duration, treatment interval, formulation and type of antimicrobial (antibiotic) are modifiable factors that will influence antimicrobial selection pressure. Currently, the impact of the route of administration on the occurrence of resistance in humans is unclear. Methods In this retrospective multi-center cohort study, we assessed the impact of different variables on antimicrobial resistance (AMR) in pathogens isolated from the urinary tract in older adults. A generalized estimating equations (GEE) model was constructed using 7397 Escherichia coli (E. coli) isolates. Results Resistance in E. coli was higher when more antibiotics had been prescribed before isolation of the sample, especially in women (significant interaction p = 0.0016) and up to nine preceding prescriptions it was lower for higher proportions of preceding parenteral prescriptions (significant interactions p = 0.0067). The laboratory identity, dying, and the time between prescription and sampling were important confounders (p < 0.001). Conclusions Our model describing shows a dose-response relation between antibiotic use and AMR in E. coli isolated from urine samples of older adults, and, for the first time, that higher proportions of preceding parenteral prescriptions are significantly associated with lower probabilities of AMR, provided that the number of preceding prescriptions is not extremely high (≥10 during the 1.5 year observation period; 93% of 5650 included patients). Trial registration Retrospectively registered.
ISSN:2047-2994