Aerobic bacterial profile and antibiotic resistance in patients with diabetic foot infections

AUTOR(ES)
FONTE

Rev. Soc. Bras. Med. Trop.

DATA DE PUBLICAÇÃO

2015-10

RESUMO

ABSTRACTINTRODUCTION: This study aimed to determine the frequencies of bacterial isolates cultured from diabetic foot infections and assess their resistance and susceptibility to commonly used antibiotics.METHODS: This prospective study included 41 patients with diabetic foot lesions. Bacteria were isolated from foot lesions, and their antibiotic susceptibility pattern was determined using the Kirby-Bauer disk diffusion method and/or broth method [minimum inhibitory concentration (MIC)].RESULTS: The most common location of ulceration was the toe (54%), followed by the plantar surface (27%) and dorsal portion (19%). A total of 89 bacterial isolates were obtained from 30 patients. The infections were predominantly due to Gram-positive bacteria and polymicrobial bacteremia. The most commonly isolated Gram-positive bacteria were Staphylococcus aureus, followed by Staphylococcus saprophyticus, Staphylococcus epidermidis, Streptococcus agalactiae, and Streptococcus pneumoniae. The most commonly isolated Gram-negative bacteria were Proteus spp. and Enterobacterspp., followed by Escherichia coli, Pseudomonasspp., and Citrobacterspp. Nine cases of methicillin-resistant Staphylococcus aureus (MRSA) had cefoxitin resistance, and among these MRSA isolates, 3 were resistant to vancomycin with the MIC technique. The antibiotic imipenem was the most effective against both Gram-positive and Gram-negative bacteria, and gentamicin was effective against Gram-negative bacteria.CONCLUSIONS: The present study confirmed the high prevalence of multidrug-resistant pathogens in diabetic foot ulcers. It is necessary to evaluate the different microorganisms infecting the wound and to know the antibiotic susceptibility patterns of the isolates from the infected wound. This knowledge is crucial for planning treatment with the appropriate antibiotics, reducing resistance patterns, and minimizing healthcare costs.

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