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

E. Geoffrey Playford, Jeffrey Lipman, Michael Jones, Anna F. Lau, Masrura Kabir, Sharon C A Chen, Deborah J. Marriott, Ian Seppelt, Thomas Gottlieb, Winston Cheung, Jonathan R. Iredell, Emma S. McBryde, Tania C. Sorrell

Research output: Contribution to journalArticleResearchpeer-review

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.

LanguageEnglish
Pages1463-1469
Number of pages7
JournalClinical Infectious Diseases
Volume63
Issue number11
DOIs
Publication statusPublished - 1 Dec 2016

Keywords

  • Candidemia
  • Critical care
  • Invasive candidiasis
  • Prophylaxis
  • Risk prediction

Cite this

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. / 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. In: Clinical Infectious Diseases. 2016 ; Vol. 63, No. 11. pp. 1463-1469.
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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",
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.",
keywords = "Candidemia, Critical care, Invasive candidiasis, Prophylaxis, Risk prediction",
author = "Playford, {E. Geoffrey} and Jeffrey Lipman and Michael Jones and Lau, {Anna F.} and Masrura Kabir and Chen, {Sharon C A} and Marriott, {Deborah J.} and Ian Seppelt and Thomas Gottlieb and Winston Cheung and Iredell, {Jonathan R.} and McBryde, {Emma S.} and Sorrell, {Tania C.}",
year = "2016",
month = "12",
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doi = "10.1093/cid/ciw610",
language = "English",
volume = "63",
pages = "1463--1469",
journal = "Clinical Infectious Diseases",
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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.; Sorrell, Tania C.

In: Clinical Infectious Diseases, Vol. 63, No. 11, 01.12.2016, p. 1463-1469.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

T1 - Problematic dichotomization of risk for intensive care unit (ICU)-acquired invasive candidiasis

T2 - Clinical Infectious Diseases

AU - Playford, E. Geoffrey

AU - Lipman, Jeffrey

AU - Jones, Michael

AU - Lau, Anna F.

AU - Kabir, Masrura

AU - Chen, Sharon C A

AU - Marriott, Deborah J.

AU - Seppelt, Ian

AU - Gottlieb, Thomas

AU - Cheung, Winston

AU - Iredell, Jonathan R.

AU - McBryde, Emma S.

AU - Sorrell, Tania C.

PY - 2016/12/1

Y1 - 2016/12/1

N2 - 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.

AB - 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.

KW - Candidemia

KW - Critical care

KW - Invasive candidiasis

KW - Prophylaxis

KW - Risk prediction

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U2 - 10.1093/cid/ciw610

DO - 10.1093/cid/ciw610

M3 - Article

VL - 63

SP - 1463

EP - 1469

JO - Clinical Infectious Diseases

JF - Clinical Infectious Diseases

SN - 1058-4838

IS - 11

ER -