Biomedizinische Forschung

Abstrakt

Emerge of non-albicans Candida species; evaluation of Candida species and antifungal susceptibilities according to years

Background: Fungal infections have become frequently identified causative agents of nosocomial infections in the recent years, leading to more common use of empirical antifungal therapies. It results in increased development of drug-resistant fungal strains and resistance. In this study, we aimed to identify the Candida species isolated from various clinical samples and examine annual distribution of susceptibility to antifungals to keep a track of local resistance rates and guide treatment planning.

Methods: A total number of 169 Candida isolates, which were isolated in the samples obtained from the patients during a period of five years. Fungal identification and antifungal susceptibility tests were performed using VITEK® 2 automated system and using the mass spectrometry (Maldi-TOF).

Results: Of the strains isolated, 91 (53.5%) were identified as C. albicans, 33 (19.5%) as C. parapsilosis, 15 (8.8%) as C. glabrata, 14 (8.2%) as C. tropicalis, 5 (2.9%) as C. kefyr, 5 (2.9%) as C. famata, 2 (1.1%) as C. lipolytica, 1 (0.5%) as C. guilliermondii, and 1 (0.5%) as C. dubliniensis. Antifungal susceptibility analyses showed that there were seven strains (4.1%) resistant to each of amphotericin B, fluconazole and flucytosine, two strains resistant to voriconazole (1.1%) and one strain resistant to caspofungin (0.5%). The annual distribution of the isolation rates showed that both C. albicans and nonalbicans species became more frequently isolated over years. All drug-resistant strains were found to emerge within the past one-year period.

Conclusion: Both C. albicans and non-albicans species have become more frequently isolated within the recent years, while all of the resistant strains developed within the past one-year period. In addition to previous studies, our study results are of utmost importance, as they likely to contribute to the local monitoring of the resistance rates as well as planning or tailoring empirical therapies.

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