Abstract

Background: As fungal infections represent a growing global health concern, particularly among vulnerable populations, and antifungal susceptibility may vary even within the same genus or species complex, accurate and rapid diagnostic tools are increasingly essential. VITEK 2 is an automated identification system based on biochemical methods and widely used in microbiology laboratories, especially in developing countries. This study aimed to retrospectively evaluate the performance and accuracy of the VITEK 2 system in identifying yeasts, particularly rare and emerging species such as Candida auris.
Methods: Data of a total of 173 yeast isolates obtained from clinical specimens were evaluated, including 96 common non-albicans Candida species, 68 rare Candida species, and nine non-Candida yeasts.
Results: Overall, 111 (64.2%) isolates were accurately identified, eight (4.6%) were misidentified, and 54 (31.2%) were not identified. Accurate identification rates for common, rare, and non-Candida species were 73.9% (71/96), 57.3% (39/68), and 11.1% (1/9), respectively. Among 44 C. auris isolates, 36 (81.8%) were accurately identified, while three (6.8%) were misidentified (two isolates as Cryptococcus laurentii and one isolate as Candida duobushaemulonii), and five (11.4%) remained unidentified.
Conclusions: In conclusion, more studies evaluating the latest versions of the VITEK 2 system, with a greater number of isolates, particularly rare yeast species, are needed.

DOI: 10.7754/Clin.Lab.2025.250953