Candidaemia: Risk factors and validity of tools to predict risk of Candidaemia in Intensive care unit patients in Teaching Hospital Karapitiya

Ceylon Med J. 2018 Dec 31;63(4):169-173. doi: 10.4038/cmj.v63i4.8767.

Abstract

Introduction: The ability to predict candidaemia gives a significant advantage to the clinician by enabling pre-emptive treatment to reduce mortality.

Objectives: To identify the prevalence, risk factors, and to validate candida colonization index (CI), candida score (CS) to reliably predict the development of candidaemia in the identified study sample.

Methods: Cross sectional analytical study of consecutive admissions fulfilling inclusion criteria to intensive care units (ICUs) of Teaching Hospital Karapitiya from 1st December 2015 to 30th March 2016. Candida colonization of non-blood body sites was measured by culture on admission and repeated every 3rd day until discharge from ICU, death or development of candidaemia. CI, corrected CI (CCI), and CS were calculated for the study patients.

Results: Candida colonization was found in 100 (65.7%) patients out of 152 patients screened. The presence of sepsis, gastro-intestinal infection or surgery, central venous line colonization, higher density of rectal, oral and urine colonization was significantly different among the infected and non-infected groups. Change of species of colonizing candida was also a significant new risk factor found in the study. All the indices and scores had excellent sensitivity and negative predictive values. However none of the scores had good specificity except for CCI, which was 94%.

Conclusions: A combination of CI, CCI and CS formulated for the study sample could reliably predict candidaemia.

Keywords: Candidaemia; Prevalence; Risk factors; Diagnosis.

MeSH terms

  • Aged
  • Bacteriological Techniques / methods
  • Bacteriological Techniques / statistics & numerical data
  • Candida* / isolation & purification
  • Candida* / pathogenicity
  • Candidemia* / diagnosis
  • Candidemia* / epidemiology
  • Cross-Sectional Studies
  • Female
  • Hospitals, Teaching / statistics & numerical data
  • Humans
  • Intensive Care Units / statistics & numerical data*
  • Male
  • Middle Aged
  • Predictive Value of Tests
  • Prevalence
  • Risk Factors
  • Sri Lanka / epidemiology