A guide to empirical management of urinary tract infection in outpatient setting in a tertiary care institute: A study from Western India.

E Rajni, K Goyal, R Sharma
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Abstract

Introduction: Urinary tract infections make up a major proportion of infections encountered in outpatient setting in hospitals. Treatment is largely based on the epidemiology of locally prevalent flora. Selection of an appropriate antibiotic is crucial, as inappropriate use could contribute to an alarming rise in antimicrobial resistance.

Materials and methods: This is a retrospective observational study conducted in a tertiary care teaching hospital. The urine samples were inoculated on cysteine lactose electrolyte-deficient (CLED) media and identification, and antimicrobial susceptibility testing of uropathogens was done using VITEK-2 system.

Results: A total of 3893 urine samples were received during the study period, out of which 293 (7.5%) samples were reported positive, including 167 (57%) females and 126 (43%) males. The most common pathogenic isolates were Escherichia coli (191, 65.1%) followed by Klebsiella pneumoniae (42, 14.3%), Enterococcus spp (20, 6.8%), and Pseudomonas aeruginosa (19, 6.4%). Cotrimoxazole resistance was observed in 52.3% Escherichia coli and 47.1% Klebsiella pneumoniae isolates. About, 100% susceptibility was observed for fosfomycin. A total of 58.1% Escherichia coli and 40.7% Klebsiella pneumoniae isolates were found to be multi-drug resistant (MDR).

Conclusion: According to this study, cotrimoxazole, cephalosporins, and fluoroquinolones need to be curtailed for empirical treatment of UTI in OPD because of high resistance. Nitrofurantoin and fosfomycin may be considered as drugs of choice for empirical therapy of lower UTIs.

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VR Khanolkar's research and academic activities in K.E.M. Hospital and Seth G.S. Medical College. A guide to empirical management of urinary tract infection in outpatient setting in a tertiary care institute: A study from Western India. Authors, beware of plagiarism in medical writing. Navigating the labyrinth: Phenotypes of IgG4-related disease. 2. Types of data and data collation for efficient processing.
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