Background and Objective: Everyone, regardless of age, is susceptible to urinary tract infections (UTIs), which rank high among bacterial infections. Uropathogens' rising resistance to standard antibiotics is a major issue in modern public health. The purpose of this research was to determine which bacteria were responsible for patients' UTIs and to assess their antibiotic susceptibility patterns so that doctors could prescribe the most effective empirical treatments.
Materials and Methods: A hospital-based cross-sectional study was conducted on 50 patients clinically diagnosed with UTIs. This study was conducted at the department of Pharmacology, I-Care Institute of Medical Sciences and Research, Balughata Rd, Haldia, West Bengal, India from March 2019 to February 2020. Midstream urine samples were collected aseptically and cultured using standard microbiological procedures. Bacterial identification was done through Gram staining and conventional biochemical tests. Antimicrobial susceptibility testing was performed using the Kirby-Bauer disk diffusion method according to Clinical and Laboratory Standards Institute (CLSI) guidelines.
Results: Out of 50 urine samples, 38 (76%) showed significant bacterial growth. The most frequently isolated pathogen was Escherichia coli (57.9%), followed by Klebsiella pneumoniae (18.4%), Pseudomonas aeruginosa (10.5%), Proteus mirabilis (7.9%), and Enterococcus faecalis (5.3%). High resistance was observed against ampicillin (81.6%) and ciprofloxacin (65.8%), while better sensitivity was noted for nitrofurantoin (73.7%), amikacin (71.1%), and imipenem (68.4%). Among Gram-positive isolates, 100% sensitivity to vancomycin and linezolid was recorded. Multidrug resistance was observed in 55.3% of the isolates.
Conclusion: The predominance of E. coli and the high rate of antimicrobial resistance among uropathogens in this study emphasize the need for regular surveillance of resistance patterns and rational use of antibiotics. Empirical treatment should be guided by local susceptibility data to ensure optimal clinical outcomes.
International Journal of Advanced Research in Medicine
