Akademik Veri Yönetim Sistemi
Archives of Basic and Clinical Research, cilt.7, sa.2, ss.110-124, 2025 (TRDizin)
Objective: A cumulative antibiogram serves as a critical tool in guiding the selection of appropriate empirical therapy, facilitating de-escalation based on susceptibility results, and shaping institutional policies to combat antibiotic resistance effectively. This study aimed to evaluate changes in antimicrobial susceptibility over the years and provide guidance to clinicians in the selection of empirical therapies. Methods: A retrospective analysis was conducted on the in vitro antimicrobial susceptibility test results of bacterial isolates obtained from clinical samples submitted to the Medical Microbiology Laboratory at Trakya University Hospital during the periods of 2015-2016 and 2022-2023. Cumulative antibiogram data were compiled in accordance with the guidelines outlined in the “Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data” (CLSI 2014, M39-A4). Results: A total of 7524 isolates (5009 Gram-negative, 2515 Gram-positive) were analyzed during the 2015-2016 period, while 5880 isolates (4202 Gram-negative, 1678 Gram-positive) were analyzed during the 2022-2023 period. In both timeframes, the most commonly isolated microorganisms were isolated from urine, blood/catheter, and wound/aspirate/tissue samples. The predominant isolates included Escherichia coli (E.coli), Klebsiella spp., and Enterococcus spp. Based on the findings, the following antimicrobials were identified as suitable for empirical treatment for E. coli infections: carbapenems and amikacin. For Klebsiella spp. infections: amikacin. For Enterococcus spp. infections: vancomycin, teicoplanin, linezolid, and tigecycline. For Acinetobacter spp. infections: combination therapy. Carbapenem susceptibility among Klebsiella spp., isolates decreased notably in 2022-2023, ranging between 55% and 62%, in contrast to higher rates observed during 2015-2016. Conclusion: The regular evaluation of hospital-based antibiogram data and the revision of empirical treatment protocols based on these findings represent a crucial strategy for effectively combating antimicrobial resistance.