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Microbiology Society, Journal of Medical Microbiology, 1(64), p. 7-17, 2015

DOI: 10.1099/jmm.0.080655-0

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Different scenarios for Candida parapsilosis fungaemia reveal high numbers of mixed C. parapsilosis and Candida orthopsilosis infections

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This paper is available in a repository.

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Abstract

Nosocomial fungal bloodstream infections (BSI) are increasing significantly in hospitalized patients and Candida parapsilosis has emerged as an important pathogen responsible for numerous outbreaks.The objective of this study was to evaluate C. parapsilosis sensu lato infection scenarios, regarding species distribution and strain relatedness. One hundred isolates of C. parapsilosis sensu lato derived from blood cultures and catheter tips were analyzed by multiplex microsatellite typing and by sequencing D1/D2 regions of the rDNA. Our results indicate that 9.5% of the patients presented infections due to C. parapsilosis + C. orthopsilosis, 57.1% due to C. parapsilosis, 28.3% due to C. orthopsilosis, and 4.8% due to C. metapsilosis. 80% of the C. parapsilosis BSIs were due to a single strain that was also identified in the catheter but, in 10% of the cases, C. parasilosis was identified in the catheter but the BSI was due to C. orthopsilosis. There is a significant probability that C. parapsilosis isolates collected from the same patient with more than 3 months interval, are a different strain (P=0.0179). Moreover, several isolates were identified persistently in the same hospital, infecting six different patients. The incidence of polyfungal BSI infections with C. orthopsilosis + C. orthopsilosis were here reported for the first time, alerting for the fact that the species that is identified in the catheter is not always the responsible for the BSI, impacting treatment strategy. The observation that strains can remain in the hospital environment for years alerts for the possible existence of reservoirs and reinforces the need of accurate genotyping tools, like the used markers, for elucidating epidemiologic associations and detecting outbreaks.