Antimicrobial resistance in urinary tract infections caused by Escherichia coli
Abstract
Urinary tract infections (UTI) are one of the most common bacterial infections in hospital and community settings requiring antimicrobial treatment. Escherichia coli (E. coli), a bacterium frequently implicated in UTI, is becoming increasingly resistant to antimicrobials. Antimicrobial resistance (AMR) reduces the effectiveness of antimicrobial agents, leading to difficulty in treatment of patients, with the potential to prolong the duration of illness and increase mortality in patients. To date in Australia, there is a paucity of data comparing resistance patterns over time for hospital- and community-acquired E. coli UTI with no published data on incidence and risk of urinary E. coli resistance in Australia. Ciprofloxacin, a high priority critically important antimicrobial, is not recommended for empirical therapy of UTI yet resistance to this antimicrobial agent is increasing. There are no systematic reviews of studies investigating ciprofloxacin resistance in hospital- and community-acquired E. coli UTI. Therefore, the research program sought to address these knowledge gaps in three separate but interrelated studies. The research described in this thesis is the first of its kind in Australia.
Read the paper
Related studies
- Horizontal gene transfer in the human gastrointestinal tract: potential spread of antibiotic resistance genes
- Mutation supply and relative fitness shape the genotypes of ciprofloxacin-resistant Escherichia coli
- Genomic Survey of E. coli From the Bladders of Women With and Without Lower Urinary Tract Symptoms
- Characterization of cefotaxime-resistant urinary Escherichia coli from primary care in South-West England 2017–18
- Fitness cost constrains the spectrum of marR mutations in ciprofloxacin-resistant Escherichia coli
- Emerging evidence-based innovative approaches to control catheter-associated urinary tract infection: a review
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.