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Prevalence of biofilms in Candida spp. bloodstream infections: A meta-analysis

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  • María Belén Atiencia-Carrera
  • Fausto Sebastián Cabezas-Mera
  • Eduardo Tejera
  • António Machado

Abstract

Context: Candida-related infections are nowadays a serious Public Health Problem emerging multidrug-resistant strains. Candida biofilm also leads bloodstream infections to invasive systemic infections. Objective: The present meta-analysis aimed to analyze Candida biofilm rate, type, and antifungal resistance among hospitalized patients between 1995 and 2020. Data sources: Web of Science, Scopus, PubMed, and Google Scholar databases were searched for English papers using the following medical subject heading terms (MESH): “invasive candidiasis”; “bloodstream infections”; “biofilm formation”; “biofilm-related infections”; “mortality”; and “prevalence”. Study selection: The major inclusion criteria included reporting the rate of biofilm formation and the prevalence of biofilm-related to Candida species, including observational studies (more exactly, cohort, retrospective, and case-control studies). Furthermore, data regarding the mortality rate, the geographical location of the study set, and the use of anti-fungal agents in clinical isolates were also extracted from the studies. Data extraction: Independent extraction of articles by 2 authors using predefined data fields, including study quality indicators. Data synthesis: A total of 31 studies from publicly available databases met our inclusion criteria. The biofilm formation in the data set varied greatly from 16 to 100% in blood samples. Most of the studies belonged to Europe (17/31) and Asia (9/31). Forest plot showed a pooled rate of biofilm formation of 80.0% (CI: 67–90), with high heterogeneity (Q = 2567.45, I2 = 98.83, τ2 = 0.150) in random effects model (p

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  • María Belén Atiencia-Carrera & Fausto Sebastián Cabezas-Mera & Eduardo Tejera & António Machado, 2022. "Prevalence of biofilms in Candida spp. bloodstream infections: A meta-analysis," PLOS ONE, Public Library of Science, vol. 17(2), pages 1-23, February.
    • Handle: RePEc:plo:pone00:0263522
    DOI: 10.1371/journal.pone.0263522
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    1. Hong, Yili, 2013. "On computing the distribution function for the Poisson binomial distribution," Computational Statistics & Data Analysis, Elsevier, vol. 59(C), pages 41-51.
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