Antimicrobial Susceptibility Profiles of Aerobic Bacteria Causing Infections at a Tertiary Care Centre
Journal: Walawalkar International Medical Journal (Vol.11, No. 1)Publication Date: 2024-10-18
Authors : Supriya Emekar Sanjay kumar More; Nitin Ambhore;
Page : 46-53
Keywords : Antimicrobial sensitivity; aerobic bacteria; multidrug resistance;
Abstract
Introduction:The multidrug resistant bacteria are of great concern.[1] Antimicrobial resistance poses a major threat to patient's treatment as it leads to increased morbidity and mortality, increased hospital stay, and severe economic loss to the patient and nation.[2] The pattern of bacteria causing these infections and their antimicrobial susceptibility profiles vary widely.[3]The present study was conducted to isolate aerobic bacterial pathogens from various specimen and to determine their antimicrobial sensitivity pattern. Material and Methods: The pathogenic aerobes from various samples were isolated. The antimicrobial sensitivity pattern was determined for these microorganisms using conventional microbiological techniques. Results: Skin and soft tissue infections (SSTIs) (n=1229, 60%) were the most common infections followed by lower respiratory tract infections (LRTIs) (n=471, 22.61%), urinary tract infections (UTIs) (n=255, 12.24%) and blood stream infections (BSIs) (n=130, 6.23%). The most common bacteria isolated were Klebsiella sp. n=641(30.77%) followed by S. aureus n=519, (24.91%), Pseudomonas sp. n=326 (15.65%), E. coli n=262(12.6%), Citrobacter sp. n=135(6.48%), Acinatobacter sp. n= 107(5.13%) and others n= 95(4.56%). The best drug combination for BSIs, LRTI, UTI and SSTIs was meropenem and vancomycin. The extended spectrum beta lactamases (ESBL) and methicillin resistant staphylococcus aureus (MRSA) were found approximately 40%. Conclusion:The results of the current study emphasize the importance of institutional antibiotic policy for the effective and timely management of patients due to increasing drug resistance profile of bacterial pathogen with regional variation.
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