Distribution of Microorganisms and Antibiotic Resistance of Gram-negative Bacteria Isolated from Urine Cultures of Intensive Care Unit Patients During the Last Four Years

• Published in: Türk yogun bakim dergisi 2022-03, Vol.20 (1), p.25
• Main Authors: İgan, Hakan, Hancı, Hayrunisa
• Format: Article
• Language: eng ; tur
• Subjects: Antibiotics; E coli; Food irradiation; Urinary tract infections
• ISSN: 2602-2974
• DOI: 10.4274/tybd.galenos.2020.33154

Objective: This study aims to determine the distribution of microorganisms isolated from urine cultures collected from patients treated in the intensive care unit (ICU) of our hospital in the last 4 years and to conduct a study on antibiotic resistance in Gram-negative bacterial isolates. Materials and Methods: In this study, the distribution of microorganisms in urine cultures sent to the microbiology laboratory of our hospital, collected from patients who stayed in the ICU between July 2014 and July 2018, and the resistance profiles of Gram-negative bacteria to antibiotics were evaluated retrospectively. Results: No microorganism growth was observed in 692 (74.4%) of 930 urine samples sent from the ICU. Sixty-three (25.6%) of the cultures positive for microorganisms were Gram-positive bacteria, 64 (26.8%) were Candida strains, and 113 (47.4%) were Gram-negative bacteria. Strains of Escherichia coli and Klebsiella pneumoniae had the highest sensitivity to the antibiotic imipenem, whereas Pseudomonas aeruginosa strains (100%) were the most sensitive to tobramycin. Proteus spp. strains were generally susceptible to antibiotics; however, a high rate of resistance was seen in Acinetobacter spp. strains. Regarding extended-spectrum beta-lactamase production, 28 E. coli (53.8%) and 13 K. pneumoniae (46.4%) strains were found to be positive. Conclusion: Our results show an increase in microbial resistance, especially among Acinetobacter strains. Variations in the results of microorganism distribution and susceptibility clearly show the importance of every center reviewing their own data to make the correct choice of an empirical treatment.