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Prevalence and antimicrobial resistance profile of pathogens isolated from patients with urine tract infections admitted to a university hospital in a medium-sized Brazilian city. | LitMetric

AI Article Synopsis

Article Abstract

This study aimed to determine the antibiotic profile of microorganisms isolated from urine samples of patients with community urine tract infections (UTI) admitted to the University Hospital of the Federal University of Sao Carlos to support an appropriate local empirical treatment. A retrospective cross-sectional study was conducted from October 2018 to October 2020. Data from 1,528 positive urine cultures for bacterial pathogens and antibiograms were tabulated. Bacterial species prevalence and their resistance profile were analyzed and compared by sex and age. For Gram-negative fermenting bacteria, resistance rates were compared between patients with previous hospitalization and the total of infections caused by this group. For comparisons, the Chi-square test was performed, using Fisher's exact test when necessary (BioEstat program, adopting p ≤ 0.05). A multivariate analysis was applied to assess the effect of the studied variables in predicting multidrug resistance. Infections were more prevalent in women and older adults. Gram-negative bacteria represented 90.44% of total cultures. In both sexes, E. coli prevalence was significantly higher in adults compared with older adults (p < 0.0001). For several antibiotics, resistance rates were higher in the older adults compared with other ages and in patients with Gram-negative fermenting infections and previous hospitalization compared with the total of infections by this group of bacteria. The closer to the hospitalization, the higher the number of antibiotics with superior resistance rates. Resistance rates for aminoglycosides, carbapenems, ceftazidime, nitrofurantoin, piperacillin+tazobactam, and fosfomycin were less than 20%, considered adequate for empirical treatment. Only hospitalization in the previous 90 days was statistically significant in predicting infections by multidrug-resistant bacteria.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10768654PMC
http://dx.doi.org/10.1590/S1678-9946202466003DOI Listing

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