Abstract
Introduction: The aim of this study was to contribute to the establishment of appropriate empirical treatment protocols by determining antibiotic susceptibility profiles of Pseudomonas aeruginosa strains isolated from bacteremia patients in intensive care units and various clinics. Materials and Methods: Antibiotic susceptibility of a total of 111 P. aeruginosa isolates isolated from the blood of inpatients in intensive care units and other services between January 2014 and July 2018 in Cumhuriyet University, Faculty of Medicine were evaluated retrospectively. In the study, the susceptibility profiles of amikacin, piperacillin-tazobactam, ceftazidime, cefepim, gentamicin, ciprofloxacin, levofloxacin, imipenem and meropenem were investigated using the automated system of Phoenix 100 (Becton Dickinson Co., Sparks, MD, USA). The results were evaluated based on the criteria of the Clinical and Laboratory Standards Institute (CLSI) for 2014 and the European Committee on Antimicrobial Susceptibility Testing (EUCAST) from 2015 onwards. Results: One hundred and eleven P. aeruginosa were isolated from blood samples, 77 from intensive care units and 34 from various services of the hospital. P. aeruginosa strains isolated from cultures have a high rate of resistance against antimicrobial agents. The highest resistance was determined for imipenem with 20.7% and the lowest resistance was determined for amikacin with 1.8%. Piperacillintazobactam, ceftazidim, cefepim, ciprofloxacin, levofloxacin, and meropenem resistance rates were 18%, 17.1%, 17.8%, 18.9%, 13.9%, 19.8% respectively. Multidrug-resistant was found to be 10.8%. This ratio was determined as 13% in intensive care units. Conclusion: Considering the current antibiotic susceptibility profiles while determining empirical treatment protocols is rather important to prevent resistance. In addition, putting forward the bacterial resistance status periodically through this type of studies, to determine the strength of existing drugs and to guide therapy, presents valuable data. Within this context, we propose that the data of our study will contribute to the current literature
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