Abstract:

Objective: Urinary tract infections (UTIs) are among the most common infections worldwide. Pseudomonas aeruginosa is thought to cause 7% to 10% of UTIs. P. aeruginosa isolates from UTIs frequently show higher levels of antibiotic resistance than E. coli isolates. The aim of this study was to retrospectively determine the antimicrobial susceptibility profile of Pseudomonas aeruginosa strains detected as causative agents of UTIs during the 11 years (2009-2019) before the coronavirus disease-19 pandemic and to reveal epidemiologic data. Methods: Between January 2009 and October 2019, retrospective data of 540 non-repetitive Pseudomonas aeruginosa strains were included in our study. For the diagnosis of UTI, results of ≥104 CFU/mL in pure culture or ≥104 CFU/mL growths of ≤2 bacterial species were accepted as positive urine culture criteria from midstream urine samples. Identification and antimicrobial resistance were determined using the Vitek 2 Compact System. The 11-year antimicrobial resistance and the three-year Minimal Inhibitory Concentration (MIC) data were extracted from the hospital automation system retrospectively. Results: Of 540 non-repetitive Pseudomonas aeruginosa strains, 226 (41.8%) were isolated from male patients and 314 (58.2%) from female patients. The mean age of the patients was 66.54±32.62 years. Co-trimoxazole and colistin were found to be the most effective antimicrobials against P. aeruginosa. Piperacillin-tazobactam combination resistance was found to be 52.59%, third-generation ceftazidime, cefoxitin, and ceftriaxone resistance rates were 48.89%, 89.13%, and 60.37%, respectively, and the fourth-generation cefepime resistance rate was 53.7%. The mic50 values of ciprofloxacin and meropenem increased in 2019 compared with 2017. Conclusion: In conclusion, although antimicrobial resistance fluctuated over the years, there was an increase pattern in MIC values over the years. An increase in MIC values in the quinolone groups should be monitored for UTI infections. Each hospital’s monitoring of antimicrobial resistance status is critical for infection control and shedding light on reasonable antibiotic use.

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