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Abstrakt

Highlight on the Multi-Drug Resistance of Enterococcus faecalis Recovered from Diabetic Foot Patients

ALbeloushi A, Elbehiry A, Marzouk E and Zahran R

Diabetic foot infections (DFIs) are a progressively serious health problem worldwide. Enterococcus faecalis (E. faecalis) is one of the most frequent bacteria in DFIs. The antibiotic resistance patterns of this bacterium remain a significant tool for monitoring infection. Therefore, our study aimed to determine the susceptibility of E. faecalis recovered from the wounds of hospitalized diabetic foot patients to various antimicrobial drugs. Fifty-two E. faecalis strains were recovered from 630 diabetic foot patients. All isolates were identified biochemically by a Vitek® 2 system and via a mass spectrometer (MALDI Biotyper). Antimicrobial sensitivity testing used Vitek 2 cards and Kirby-Bauer as the reference method. The findings indicated that the susceptibility of E. faecalis was 100% for ampicillin, ampicillin-sulbactam, benzylpenicillin, norfloxacin, and ofloxacin; 92% for nitrofurantoin, teicoplanin, and vancomycin; 87% for imipenem; 81% for kanamycin (high concentration) and tetracycline; 73% for levofloxacin; and 52% for streptomycin (high concentrations). The resistance was 100% for clindamycin and quinupristin-dalfopristin, 96% for cefuroxime, 90% for ciprofloxacin and erythromycin, 86% for trimethoprim-sulfamethoxazole, 54% for gentamicin (high concentration), and 48% for streptomycin (high concentration). All E. faecalis strains were resistant against numerous antibiotics with a multiple antibiotic resistance (MAR) index of 0.20-0.60. The mean value of MAR indices for all tested E. faecalis species was 0. 373. The high levels of antimicrobial resistance patterns to E. faecalis seen here are important because they restrict treatment possibilities and adversely affect the health of diabetic foot patients. Consequently, our findings should be carefully considered in public health and awareness programs.

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