Evaluation of Antimicrobial Resistance in Staphylococcus aureus Isolates by Years

Interdiscip Perspect Infect Dis. 2016:2016:9171395. doi: 10.1155/2016/9171395. Epub 2016 May 9.

Abstract

Objective. Recently, community and hospital-acquired infections with Staphylococcus aureus have increased and raised antibiotic resistant isolates. In this study, we aimed to evaluate the antibiotic resistance profile of S. aureus isolates over several years in various clinical specimens from our hospital. Materials and Methods. S. aureus strains from 2009 to 2014 were isolated from various clinical samples at Yuzuncu Yil University, Dursun Odabas Medical Center, Microbiology Laboratory, and their antibiotic susceptibility test results were retrospectively investigated. The isolates were identified by conventional methods, and antibiotic susceptibility tests were performed by the Phoenix (Becton Dickinson, USA) automated system method according to Clinical and Laboratory Standards Institute (CLSI) standards. Results. A total of 1,116 S. aureus isolates were produced and methicillin-resistant S. aureus (MRSA) to 21% of all S. aureus isolates between 2009 and 2014. According to the results of susceptibility tests of all isolates of S. aureus, they have been identified as sensitive to vancomycin, daptomycin, linezolid, and levofloxacin. While the resistance rates to nitrofurantoin, quinupristin-dalfopristin, and trimethoprim-sulfamethoxazole were determined as 0.3%, 2.4%, and 6%, respectively, resistance rates to penicillin, erythromycin, rifampicin, gentamicin, and clindamycin were determined as 100%, 18%, 14%, 14%, and 11%, respectively. The highest percentage of methicillin resistance was determined as 30% in 2009, and the resistance was determined to have decreased in subsequent years (20%, 16%, 13%, 19%, and 21%) (p < 0.001). Conclusion. Currently, retrospective evaluations of causes of nosocomial infection should be done periodically. We think that any alteration of resistance over the years has to be identified, and all centers must determine their own resistance profiles, in order to guide empirical therapies. Reducing the rate of antibiotic resistance will contribute to reducing the cost of treatment.