E Geoffrey Playford1,2, Jeffrey Lipman3,4, Michael Jones5, Anna F Lau6, Masrura Kabir6, Sharon C-A Chen7,8, Deborah J Marriott9, Ian Seppelt10, Thomas Gottlieb11, Winston Cheung12, Jonathan R Iredell6,13, Emma S McBryde14, Tania C Sorrell6,13. 1. Infection Management Services, Princess Alexandra Hospital. 2. School of Medicine, University of Queensland. 3. Department of Intensive Care, Royal Brisbane and Women's Hospital. 4. University of Queensland, Brisbane. 5. Psychology Department, Macquarie University, Sydney. 6. Centre for Infectious Diseases and Microbiology, Westmead Institute for Medical Research. 7. Centre for Infectious Diseases and Microbiology Laboratory Services, Institute for Clinical Pathology and Medical Research, Westmead Hospital. 8. Sydney Medical School, University of Sydney. 9. Department of Microbiology and Infectious Diseases, St Vincent's Hospital. 10. Department of Intensive Care Medicine, Nepean Hospital, University of Sydney. 11. Department of Microbiology and Infectious Diseases. 12. Department of Intensive Care Medicine, Concord Hospital. 13. Department of Marie Bashir Institute for Infectious Diseases and Biosecurity, University of Sydney. 14. Department of Victorian Infectious Diseases Service, Royal Melbourne Hospital, University of Melbourne, Australia.
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.
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.
Authors: Lisa M Mayer; Jeffrey R Strich; Sameer S Kadri; Michail S Lionakis; Nicholas G Evans; D Rebecca Prevots; Emily E Ricotta Journal: Open Forum Infect Dis Date: 2022-08-03 Impact factor: 4.423
Authors: Adriana M Rauseo; Abdullah Aljorayid; Margaret A Olsen; Lindsey Larson; Kim L Lipsey; William G Powderly; Andrej Spec Journal: Med Mycol Date: 2021-11-03 Impact factor: 3.747