Problematic dichotomization of risk for Intensive Care Unit (ICU)-acquired invasive candidiasis: results using a risk-predictive model to categorize 3 levels of risk from a multicenter prospective cohort of Australian ICU patients

Playford, E. Geoffrey, Lipman, Jeffrey, Jones, Michael, Lau, Anna F., Kabir, Masrura, Chen, Sharon C. -A., Marriott, Deborah J., Seppelt, Ian, Gottlieb, Thomas, Cheung, Winston, Iredell, Jonathan R., McBryde, Emma S. and Sorrell, Tania C. (2016) Problematic dichotomization of risk for Intensive Care Unit (ICU)-acquired invasive candidiasis: results using a risk-predictive model to categorize 3 levels of risk from a multicenter prospective cohort of Australian ICU patients. Clinical Infectious Diseases, 63 11: 1463-1469. doi:10.1093/cid/ciw610


Author Playford, E. Geoffrey
Lipman, Jeffrey
Jones, Michael
Lau, Anna F.
Kabir, Masrura
Chen, Sharon C. -A.
Marriott, Deborah J.
Seppelt, Ian
Gottlieb, Thomas
Cheung, Winston
Iredell, Jonathan R.
McBryde, Emma S.
Sorrell, Tania C.
Title Problematic dichotomization of risk for Intensive Care Unit (ICU)-acquired invasive candidiasis: results using a risk-predictive model to categorize 3 levels of risk from a multicenter prospective cohort of Australian ICU patients
Journal name Clinical Infectious Diseases   Check publisher's open access policy
ISSN 1058-4838
1537-6591
Publication date 2016-12-01
Sub-type Article (original research)
DOI 10.1093/cid/ciw610
Open Access Status Not yet assessed
Volume 63
Issue 11
Start page 1463
End page 1469
Total pages 7
Place of publication Cary, NC, United States
Publisher Oxford University Press
Language eng
Subject 2726 Microbiology (medical)
2725 Infectious Diseases
Abstract Background. Delayed antifungal therapy for invasive candidiasis (IC) contributes to poor outcomes. Predictive risk models may allow targeted antifungal prophylaxis to those at greatest risk. Methods. A prospective cohort study of 6685 consecutive nonneutropenic patients admitted to 7 Australian intensive care units (ICUs) for ≥72 hours was performed. Clinical risk factors for IC occurring prior to and following ICU admission, colonization with Candida species on surveillance cultures from 3 sites assessed twice weekly, and the occurrence of IC ≥72 hours following ICU admission or ≤72 hours following ICU discharge were measured. From these parameters, a risk-predictive model for the development of ICU-acquired IC was then derived. Results. Ninety-six patients (1.43%) developed ICU-acquired IC. A simple summation risk-predictive model using the 10 independently significant variables associated with IC demonstrated overall moderate accuracy (area under the receiver operating characteristic curve = 0.82). No single threshold score could categorize patients into clinically useful high- and low-risk groups. However, using 2 threshold scores, 3 patient cohorts could be identified: those at high risk (score ≥6, 4.8% of total cohort, positive predictive value [PPV] 11.7%), those at low risk (score ≤2, 43.1% of total cohort, PPV 0.24%), and those at intermediate risk (score 3-5, 52.1% of total cohort, PPV 1.46%). Conclusions. Dichotomization of ICU patients into high- and low-risk groups for IC risk is problematic. Categorizing patients into high-, intermediate-, and low-risk groups may more efficiently target early antifungal strategies and utilization of newer diagnostic tests.
Formatted abstract
Background: Delayed antifungal therapy for invasive candidiasis (IC) contributes to poor outcomes. Predictive risk models may allow targeted antifungal prophylaxis to those at greatest risk.

Methods: A prospective cohort study of 6685 consecutive nonneutropenic patients admitted to 7 Australian intensive care units (ICUs) for ≥72 hours was performed. Clinical risk factors for IC occurring prior to and following ICU admission, colonization with Candida species on surveillance cultures from 3 sites assessed twice weekly, and the occurrence of IC ≥72 hours following ICU admission or ≤72 hours following ICU discharge were measured. From these parameters, a risk-predictive model for the development of ICU-acquired IC was then derived.

Results: Ninety-six patients (1.43%) developed ICU-acquired IC. A simple summation risk-predictive model using the 10 independently significant variables associated with IC demonstrated overall moderate accuracy (area under the receiver operating characteristic curve = 0.82). No single threshold score could categorize patients into clinically useful high- and low-risk groups. However, using 2 threshold scores, 3 patient cohorts could be identified: those at high risk (score ≥6, 4.8% of total cohort, positive predictive value [PPV] 11.7%), those at low risk (score ≤2, 43.1% of total cohort, PPV 0.24%), and those at intermediate risk (score 3–5, 52.1% of total cohort, PPV 1.46%).

Conclusions: Dichotomization of ICU patients into high- and low-risk groups for IC risk is problematic. Categorizing patients into high-, intermediate-, and low-risk groups may more efficiently target early antifungal strategies and utilization of newer diagnostic tests.
Keyword Invasive candidiasis
Risk prediction
Critical care
Prophylaxis
Candidemia
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
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