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. Clin Infect Dis (2016) 63 (11): 1463-1469. doi.org/10.1093/cid/ciw610 .Published: 06 September 2016
Delayed antifungal therapy for invasive candidiasis (IC) contributes to poor outcomes. Predictive risk models may allow targeted antifungal prophylaxis to those at greatest risk.
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.
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%).
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.