Performance of Chromogenic Candida Lab-Agar® Medium in Presumptive Identification of Candida Species from Clinical Samples at Sourô Sanou University Hospital of Bobo-Dioulasso, Burkina Faso

Author:

Nakanabo Diallo Seydou,Yerbanga Isidore W.,Bado Bassirou,Mandy Isidore,Anantharajah Ahalieyah,Montesinos Isabel,Denis Olivier,Bamba Sanata,Rodriguez-Villalobos Hector

Abstract

Introduction: The incidence of Candida infections is increasing worldwide. In clinical laboratories of resource-constrained countries, Candida speciation is commonly limited to germ tube tests and culture onto a chromogenic medium. In this study, we evaluated the diagnostic performance of Chromogenic Candida Lab-Agar® (CCL) in identifying Candida species from clinical samples. Methods: We evaluated the diagnostic performance of CCL with 83 yeast isolates collected from 73 clinical samples at the laboratory department of Sourô Sanou University Hospital of Bobo-Dioulasso, Burkina Faso. Clinical specimens included vaginal swabs, urine, and blood cultures. After preliminary isolation on Sabouraud chloramphenicol agar, yeast isolates were inoculated onto the CCL medium and incubated at 35 °C for 48 h. Matrix-assisted laser desorption/ionisation time of flight mass spectrometry (MALDI-TOF MS) and ribosomal DNA internal transcribed spacer (ITS) sequencing were used as reference methods. Results: Among yeast species, Candida albicans was the most prevalent (43.4%), followed by C. krusei (13.3%), C. glabrata (12.0%), C. kefyr (8.4%), and C. tropicalis (7.2%). The overall agreement rate of CCL was 56.6% and varied across Candida species; it was 94.4% for C. albicans, 50% for C. glabrata, 18.2% for C. krusei, and 33.3% for C. tropicalis. Conclusions: This study showed that CCL had moderate accuracy in identifying Candida at the species level from clinical specimens in a routine laboratory in Burkina Faso. The misidentification of non-albicans species may expose patients to inadequate antifungal treatment. Therefore, identifying yeast in a routine based on CCL is not enough and should be associated with more accurate methods.

Publisher

MDPI AG

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