Margherita Scapaticci1, Andrea Bartolini2, Federica Del Chierico3, Cristel Accardi4, Francesco Di Girolamo4, Andrea Masotti5, Maurizio Muraca6, Lorenza Putignani7. 1. PhD, Laboratory Medicine Department, San Camillo Hospital, Viale Vittorio Veneto 18, 31100, Treviso, Italy. 2. MD, Laboratory Medicine Department, San Camillo Hospital, Viale Vittorio Veneto 18, 31100, Treviso, Italy. 3. PhD, Unit of Human Microbiome, Children's Hospital and Research Institute Bambino Gesú, Piazza Sant'Onofrio 4, Rome, 00165, Italy. 4. Unit of Human Microbiome, Children's Hospital and Research Institute Bambino Gesú, Piazza Sant'Onofrio 4, Rome, 00165, Italy. 5. PhD, Gene Expression-Microarrays Laboratory, Bambino Gesú Children's Hospital, IRCCS, Piazza Sant'Onofrio 4 Rome 00165, Italy. 6. MD, Department of Women's and Children's Health University of Padova, Via Giustiniani 3, Padova, Italy. 7. PhD, Unit of Parasitology, Children's Hospital and Research Institute Bambino Gesú, Piazza Sant'Onofrio 4, Rome, 00165, Italy.
Abstract
INTRODUCTION: Yeast pathogens are emerging agents of nosocomial as well as community-acquired infections and their rapid and accurate identification is crucial for a better management of high-risk patients and for an adequate treatment. METHODS: We performed a retrospective review of 156 yeast isolates collected during a 17 months' period of regular clinical practice at the Microbiology Department of San Camillo Hospital in Treviso, Italy and analyzed by the traditional culture-based method combined with matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). RESULTS: Out of all the samples collected MALDI-TOF MS was able to characterize with a MT score ≥1.7 (accurate result at species level) 12 different yeast and yeast-like species from 140 samples: Candida albicans (63.7%), Candida glabrata (13.6%), Saccharomyces cerevisiae (6.5%), Candida parapsilosis (5.7%), Candida tropicalis (2.1%), Candida pararugosa (2.1%), Candida guilliermondii (2.1%), Candida kefyr (1.4%), Candida lusitaniae (0.7%), Candida palmioleophila (0.7%), Geotrichum silvicola (0.7%), Rhodotorula mucilaginosa (0.7%). Susceptibility testing toward seven common antifungal agents showed a characteristic MIC distribution of C. albicans isolates for echinocandins: particularly we noticed that 72% and 46% of C. albicans showed an MIC value close to clinical breakpoint as defined by EUCAST, respectively for anidulafungin and micafungin. CONCLUSION: Accurate identification of microorganisms and the study of their antifungal susceptibility allow to understand the epidemiology of a particular area, permitting the choice of the most appropriate early antifungal treatment.
INTRODUCTION: Yeast pathogens are emerging agents of nosocomial as well as community-acquired infections and their rapid and accurate identification is crucial for a better management of high-risk patients and for an adequate treatment. METHODS: We performed a retrospective review of 156 yeast isolates collected during a 17 months' period of regular clinical practice at the Microbiology Department of San Camillo Hospital in Treviso, Italy and analyzed by the traditional culture-based method combined with matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). RESULTS: Out of all the samples collected MALDI-TOF MS was able to characterize with a MT score ≥1.7 (accurate result at species level) 12 different yeast and yeast-like species from 140 samples: Candida albicans (63.7%), Candida glabrata (13.6%), Saccharomyces cerevisiae (6.5%), Candida parapsilosis (5.7%), Candida tropicalis (2.1%), Candida pararugosa (2.1%), Candida guilliermondii (2.1%), Candida kefyr (1.4%), Candida lusitaniae (0.7%), Candida palmioleophila (0.7%), Geotrichum silvicola (0.7%), Rhodotorula mucilaginosa (0.7%). Susceptibility testing toward seven common antifungal agents showed a characteristic MIC distribution of C. albicans isolates for echinocandins: particularly we noticed that 72% and 46% of C. albicans showed an MIC value close to clinical breakpoint as defined by EUCAST, respectively for anidulafungin and micafungin. CONCLUSION: Accurate identification of microorganisms and the study of their antifungal susceptibility allow to understand the epidemiology of a particular area, permitting the choice of the most appropriate early antifungal treatment.
Authors: O A Cornely; M Bassetti; T Calandra; J Garbino; B J Kullberg; O Lortholary; W Meersseman; M Akova; M C Arendrup; S Arikan-Akdagli; J Bille; E Castagnola; M Cuenca-Estrella; J P Donnelly; A H Groll; R Herbrecht; W W Hope; H E Jensen; C Lass-Flörl; G Petrikkos; M D Richardson; E Roilides; P E Verweij; C Viscoli; A J Ullmann Journal: Clin Microbiol Infect Date: 2012-12 Impact factor: 8.067
Authors: Katherine K Perez; Randall J Olsen; William L Musick; Patricia L Cernoch; James R Davis; Geoffrey A Land; Leif E Peterson; James M Musser Journal: Arch Pathol Lab Med Date: 2012-12-06 Impact factor: 5.534