Evaluation of New Colorimetric Vitek 2 Yeast Identification Card by Use of Different Source Media

Valenza, Giuseppe; Strasen, Jörn; Schäfer, Frauke; Frosch, Matthias; Kurzai, Oliver; Abele‐Horn, Marianne

doi:10.1128/jcm.01318-08

Cited by 38 publications

(26 citation statements)

References 10 publications

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“…The main characteristics of the 26 studies (32-57), which were published between 1993 and 2014, are shown in Table 1 (see also Table S2 in the supplemental material). Among the 26 studies, 12 (32-34, 36-38, 40-43, 45, 54) reported on the identification performance of the AuxaColor system, 5 (35,38,39,43,54) reported on the identification performance of the API ID32C system, and 13 (44,(46)(47)(48)(49)(50)(51)(52)(53)(54)(55)(56)(57) reported on the identification performance of the Vitek 2 system operating with the ID-YST (fluorimetric) card (44,(46)(47)(48)(49) and/or the YST (colorimetric) card (47,48,(50)(51)(52)(53)(54)(55)(56)(57); among them, three were direct-comparison studies, of which two were between the AuxaColor and API ID32C systems (38,43) and one was among the AuxaColor, API ID32C, and Vitek 2 systems (54). Two studies evaluating the Vitek 2 system compared the colorimetric YST card with the older fluorimetric ID-YST card (47,48); however, we decided to include the results of these studies only with respect to the YST card.…”

Section: Resultsmentioning

confidence: 99%

“…The majority of the included studies (20 of 26 studies [65.4%]) used phenotypic identification methods, consist-ing of biochemical, morphological, or physiological tests, as reference methods. In 3 of these studies (46,48,52), phenotypic methods were used in conjunction with molecular methods (i.e., sequencing of the internal transcribed spacer [ITS] region or the 18S-28S intersequence of ribosomal DNA [rDNA]) but only to resolve discrepant results between two phenotypic methods (i.e., the method under evaluation and that used as the reference method). Among the studies that employed molecular methods as reference methods (35,51,(53)(54)(55)(56), one study employed multilocus microsatellite-based PCR fingerprinting, and rDNA sequencing of all isolates was performed in the other 5 studies.…”

Section: Resultsmentioning

confidence: 99%

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Are the Conventional Commercial Yeast Identification Methods Still Helpful in the Era of New Clinical Microbiology Diagnostics? A Meta-Analysis of Their Accuracy

et al. 2015

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Accurate identification of pathogenic species is important for early appropriate patient management, but growing diversity of infectious species/strains makes the identification of clinical yeasts increasingly difficult. Among conventional methods that are commercially available, the API ID32C, AuxaColor, and Vitek 2 systems are currently the most used systems in routine clinical microbiology. We performed a systematic review and meta-analysis to estimate and to compare the accuracy of the three systems, in order to assess whether they are still of value for the species-level identification of medically relevant yeasts. After adopting rigorous selection criteria, we included 26 published studies involving Candida and non-Candida yeasts that were tested with the API ID32C (674 isolates), AuxaColor (1,740 T he epidemiology of yeast infections, particularly those involving the bloodstream (i.e., fungemia) or other normally sterile sites, continues to evolve throughout the world (1), likely due to the diversity of susceptible hosts, including mainly patients undergoing transplantations or receiving treatment for underlying malignant diseases (2). Prophylactic use of antifungals has also contributed to alterations in the patterns of such infections, leading to increases in the incidence of non-albicans Candida species, compared to Candida albicans (3-6). Although the latter species is the most frequently isolated yeast in hospital settings (7), the emergence of less-common or "cryptic" non-albicans Candida species, as well as uncommon yeasts such as Rhodotorula, Geotrichum, Pichia, Malassezia, Saccharomyces, and cryptococci other than Cryptococcus neoformans (8), poses a threat due to their potential to develop antifungal resistance (9-12) or their intrinsically decreased susceptibility to one or more antifungal agents (13-15). As differences in antifungal drug susceptibilities can exist not only among genera but also among members of the same genus or species complex (8), accurate species identification is important for initiating early effective antifungal therapy, especially when susceptibility testing results are not promptly available.As simple, rapid, reliable alternatives to traditional methods based on the Wickerham assimilation/fermentation patterns (16), manual (e.g., AuxaColor [Bio-Rad, Marnes-la-Coquette, France]) and automated (i.e., Vitek 2 [bioMérieux, Marcy l'Etoile, France]) commercial identification systems are currently being used in clinical microbiology laboratories, but their ability to identify yeast isolates to the species level is dependent on the types and numbers of biochemical (carbohydrate/enzyme) substrates tested (17). Although with a limited database of only 26 taxa/species (updated to include 33 yeast species in a newer version of the system [AuxaColor 2], which was launched in 2002), the AuxaColor system uses colorimetric tests for assimilation substrates,

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Are the Conventional Commercial Yeast Identification Methods Still Helpful in the Era of New Clinical Microbiology Diagnostics? A Meta-Analysis of Their Accuracy

et al. 2015

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“…Second, a significant proportion of commonly occurring errors (underlined in Table 4) would likely have been avoided if referring laboratories had performed Dalmau cultures (or similar cultures) and had examined the isolates for the ability to produce simple morphological features such as pseudohyphae, true hyphae, arthrospores, capsules, or chlamydospores. Indeed, examination of isolates grown on morphological agars is required to generate full identification profiles on many ID systems (for example, see references 7 and 33) and is recommended to increase the robustness of identification in the case of low discrimination results in most phenotypic ID systems (34,35). Third, 33 of the errors involved common organisms that had been identified as yeast species that are encountered only extremely rarely in the clinical setting: erroneous identifications of Candida famata (n ϭ 20), Cryptococcus laurentii (n ϭ 5); Candida ciferii (n ϭ 3), Candida sphaerica (n ϭ 3), and Zygosaccharomyces spp.…”

Section: Resultsmentioning

confidence: 99%

“…Previous studies have demonstrated that such methods can fail to identify the less common pathogens and those common organisms that are not behaving as expected (9,14,15,34,35) or to discriminate between closely related species (4,9,14,15). Moreover, the accuracy of such commercial systems is greatly reduced if laboratories do not perform the specialized cultures necessary to assess the additional morphological characteristics required for complete identification profiles (MRL, unpublished data).…”

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confidence: 99%

Assessment of Accuracy of Identification of Pathogenic Yeasts in Microbiology Laboratories in the United Kingdom

Borman¹,

Székely²,

Palmer³

et al. 2012

J Clin Microbiol

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Here, we present the results of a 12-month evaluation of the accuracy of identifications that accompany yeast isolates submitted to the Mycology Reference Laboratory (United Kingdom) for either confirmation of identity or susceptibility testing. In total, 1,781 yeast isolates were analyzed, and the robustness of prior identifications obtained in microbiology laboratories throughout the United Kingdom was assessed using a combination of culture on chromogenic agar, morphology on cornmeal agar, and molecular identification by pyrosequencing. Over 40% of isolates (755) were submitted without any suggested identification. Of those isolates with a prior identification, 100 (9.7%) were incorrectly identified. Error rates ranged from 5.2% (for organisms submitted for antifungal susceptibility testing) to 18.2% (for organisms requiring confirmation of identity) and varied in a strictly species-specific manner. At least 50% of identification errors would be likely to affect interpretation of MIC data, with a possible impact on patient management. In addition, 2.3% of submitted cultures were found to contain mixtures of at least two yeast species. The vast majority of mixtures had gone undetected in the referring laboratory and would have impacted the interpretation of antifungal susceptibility profiles and patient management. Some of the more common misidentifications are discussed according to the identification method employed, with suggestions for avoiding such misinterpretations.

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“…The most common species misidentified by PI were C. tropicalis (n ϭ 7) and then C. albicans (n ϭ 3), which may have resulted in inappropriate antifungal therapy. Commercial yeast identification systems such as Vitek 2 have been shown to be less satisfactory at identifying C. tropicalis (12), while CHROMagar Candida has been shown to be useful for identification of C. albicans and C. tropicalis (13). In this study, the misidentification rate for BSI yeasts of C. albicans and C. tropicalis was 0% (0/75) in three hospitals (hospitals B, H, and I) which had used CHROMagar routinely but 4.1% (10/241) in seven other hospitals.…”

mentioning

confidence: 99%

Accuracy of Species-Level Identification of Yeast Isolates from Blood Cultures from 10 University Hospitals in South Korea by Use of the Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry-Based Vitek MS System

et al. 2013

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eWe assessed the accuracy of yeast bloodstream isolate identification performed over a 1-year period at 10 South Korean hospitals, using the matrix-assisted laser desorption ionization-time of flight (MALDI-TOF)-based Vitek MS system. The overall phenotypic misidentification rate was 3.4% (18/533), with considerable variation between hospitals (0.0% to 19.0%), compared to 1.1% (6/533) for the Vitek MS system.

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Evaluation of New Colorimetric Vitek 2 Yeast Identification Card by Use of Different Source Media

Cited by 38 publications

References 10 publications

Are the Conventional Commercial Yeast Identification Methods Still Helpful in the Era of New Clinical Microbiology Diagnostics? A Meta-Analysis of Their Accuracy

Are the Conventional Commercial Yeast Identification Methods Still Helpful in the Era of New Clinical Microbiology Diagnostics? A Meta-Analysis of Their Accuracy

Assessment of Accuracy of Identification of Pathogenic Yeasts in Microbiology Laboratories in the United Kingdom

Accuracy of Species-Level Identification of Yeast Isolates from Blood Cultures from 10 University Hospitals in South Korea by Use of the Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry-Based Vitek MS System

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