ISSN: 2332-0877

Zeitschrift für Infektionskrankheiten und Therapie

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Abstrakt

Analysis of Microbial Resistance and Prescription Preferences using Antibiograms

Inderpal Kaur, Inderpal singh grover, Jasmeet Singh, Kunwar Harsh Upveja and Sukrita Paul

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.

Haftungsausschluss: Dieser Abstract wurde mit Hilfe von Künstlicher Intelligenz übersetzt und wurde noch nicht überprüft oder verifiziert.