Individual risk factors and critical care unit effects on Invasive Candida Infection occurring in critical care units in the UK: A multilevel model

Lynsey Patterson, Ronan McMullan, David A. Harrison

Research output: Contribution to journalArticlepeer-review

Abstract

Geographical variation is observed in invasive candida infection (ICI) and differences between critical care units (CCUs) may contribute. To examine rates, risk factors and individual and unit-level variation of ICI in UK CCUs. Data from the Fungal Infection Risk Evaluation Study was used to examine individuals admitted to 96 CCUs in the UK; July 2009-March 2011. Cases were non-neutropenic individuals aged 18 years and over with ICI identified after admission. Mixed-effects Poisson regression models adjusted for the CCU. There were 225 cases of ICI, a rate of 6.84/10 000 bed days and a threefold variation between the lowest and highest UK regions. Independent risk factors included abdominal surgery (adjusted incidence rate ratio (AIRR) 2.03 95% CI 1.49, 2.76), parenteral nutrition (AIRR 1.89 95% CI 1.33, 2.70), fungal colonisation at two or more sites (AIRR 2.30 95% CI 1.34, 3.95) and indwelling devices. Approximately 4% of the variation in ICI rates could be attributed to the CCU. We identified independent risk factors for ICI and showed, for the first time, that the critical care unit effect was small. Despite this, future studies should consider the hierarchical structure of the data to ensure robust estimates.

Original languageEnglish
Pages (from-to)790-795
Number of pages6
JournalMycoses
Volume62
Issue number9
Early online date20 Jun 2019
DOIs
Publication statusPublished - Sept 2019
Externally publishedYes

Bibliographical note

© 2019 Blackwell Verlag GmbH.

Keywords

  • Aged
  • Antifungal Agents/therapeutic use
  • Candidiasis/drug therapy
  • Candidiasis, Invasive/drug therapy
  • Cohort Studies
  • Critical Care/standards
  • Female
  • Hospitalization
  • Humans
  • Incidence
  • Intensive Care Units
  • Male
  • Middle Aged
  • Models, Statistical
  • Regression Analysis
  • Risk Factors
  • United Kingdom

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