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Hindi Research Article
Analysis of Microbial Resistance and Prescription Preferences using Antibiograms
Inderpal Kaur*, Inderpal singh grover, Jasmeet Singh, Kunwar Harsh Upveja and Sukrita PaulGovernment Medical College, Amritsar, India
- *Corresponding Author:
- Dr. Inderpal Kaur MD
Department of Pharmacology, Government Medical College, Amritsar, India
Tel: +919501004136
E-mail: inderpalpharma@gmail.com
Received date: September 29, 2016; Accepted date: October 24, 2016; Published date: October 26, 2016
Citation: Kaur I, Grover IS, Singh J, Upveja KH, Paul S (2016) Analysis of Microbial Resistance and Prescription Preferences using Antibiograms. J Infect Dis Ther 4:302. doi:10.4172/2332-0877.1000302
Copyright: © 2016 Kaur I, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Introduction: Hospital antibiogram is a periodic summary of antimicrobial susceptibilities of local bacterial isolates submitted to the hospital's clinical microbiology laboratory. It not only aids clinicians to select the most appropriate empiric therapy, but also in monitoring resistance trends within an institution, thereby optimizing treatment.
Aims: To analyze the susceptibility trends of microbes by using antibiograms; assess the modification in prescribing empirical therapy and examine application of the susceptibility report in clinical practice.
Settings and design: A retrospective study of culture sensitivity reports and indoor prescriptions from departments of Medicine, Pulmonary medicine, Surgery, Orthopaedics, Obstetrics and Gynaecology and Intensive Care Unit.
Methods and material: Culture sensitivity reports of samples collected from these specialties were analyzed for the susceptibility pattern of antibiotics. In addition, prescriptions were analysed for the prescribing patterns for antimicrobials.
Statistical analysis used: The data was tabulated using Microsoft Office Excel 2010 and were later compiled to make an antibiogram. Chi-square values were calculated using online software Graphpad Quickcalcs.
Results: After analysing the data it was found that the most common infecting organisms were Pseudomonas aeruginosa, Escherichia coli and Staphylococcus aureus susceptible to amikacin, piperacillin/tazobactam and linezolid. However the prescriptions analysed revealed that the commonly prescribed drugs were ceftriaxone and amoxycillin/clavulanic acid.
Conclusions: Antibiogram is useful in predicting and monitoring the trends of antimicrobial resistance. The survey revealed a clear mismatch between the sensitivity reports and the prescribing trends which can lead to evolution of multi-drug resistant organisms.
