Antimicrobial Susceptibility Patterns among Urinary Bacterial Isolates: A Descriptive Analysis of Ten Consecutive Clinical Cases

Abstract

Background: Antimicrobial resistance (AMR) is an emerging clinical problem among urinary pathogens and poses a challenge to empirical therapy. This descriptive analysis summarised antimicrobial susceptibility testing of 10 consecutive bacterial isolates obtained from urine samples at a single diagnostic microbiology laboratory. Methods: The methods consisted of a review of 10 de-identified antimicrobial susceptibility testing (AST) reports of urinary isolates. Data on organism identification, minimum inhibitory concentration (MIC), and susceptibility interpretation, based on Clinical and Laboratory Standards Institute (CLSI) breakpoints, were retrieved and analysed descriptively. Results: The isolates comprised 6 Gram-negative organisms (Klebsiella pneumoniae (n=3), Escherichia coli (n=2), Proteus spp. (n=1)) and 4 Gram-positive cocci (Staphylococcus aureus (n=2), S. haemolyticus (n=1), S. epidermidis (n=1)). Methicillin resistance was observed in all four staphylococcal isolates, and all were susceptible to linezolid, teicoplanin, and tigecycline. Among the Gram-negative isolates, 4/6 (66.7%) had an extended-spectrum beta-lactamase (ESBL)-like phenotype (resistance to cefotaxime, ceftazidime, and/or cefepime). One Klebsiella pneumoniae isolate was resistant to ceftazidime-avibactam and intermediate to imipenem, while no carbapenem resistance was observed. Trimethoprim-sulfamethoxazole resistance was common in both groups. The most active agents against the Gram-negative isolates, as in the Gram-positive isolates, were aminoglycosides, tigecycline, and carbapenems. Conclusions: This small case series highlights a substantial degree of methicillin resistance among uropathogenic staphylococci and a high frequency of an ESBL-like phenotype among the Enterobacteriaceae; carbapenems, aminoglycosides, tigecycline, linezolid, and teicoplanin were generally active. Larger prospective surveillance studies linked to demographic data are necessary to validate these results and inform local empirical prescribing.