Literature DB >> 27601224

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 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.   

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.
© The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail journals.permissions@oup.com.

Entities:  

Keywords:  candidemia; critical care; invasive candidiasis; prophylaxis; risk prediction

Mesh:

Substances:

Year:  2016        PMID: 27601224     DOI: 10.1093/cid/ciw610

Source DB:  PubMed          Journal:  Clin Infect Dis        ISSN: 1058-4838            Impact factor:   9.079


  10 in total

1.  Machine Learning in Infectious Disease for Risk Factor Identification and Hypothesis Generation: Proof of Concept Using Invasive Candidiasis.

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

2.  Development and Validation of a Risk Score for Predicting Invasive Candidiasis in Intensive Care Unit Patients by Incorporating Clinical Risk Factors and Lymphocyte Subtyping.

Authors:  Jiahui Zhang; Wei Cheng; Dongkai Li; Jianwei Chen; Guoyu Zhao; Hao Wang; Na Cui
Journal:  Front Cell Infect Microbiol       Date:  2022-04-27       Impact factor: 6.073

3.  Modified Pitt bacteremia score for predicting mortality in patients with candidaemia: A multicentre seven-year retrospective study conducted in Japan.

Authors:  Nana Nakada-Motokawa; Taiga Miyazaki; Takashi Ueda; Yuka Yamagishi; Koichi Yamada; Hideki Kawamura; Hiroshi Kakeya; Hiroshi Mukae; Hiroshige Mikamo; Yoshio Takesue; Shigeru Kohno
Journal:  Mycoses       Date:  2021-10-23       Impact factor: 4.931

Review 4.  Non-Culture Diagnostics for Invasive Candidiasis: Promise and Unintended Consequences.

Authors:  Cornelius J Clancy; M Hong Nguyen
Journal:  J Fungi (Basel)       Date:  2018-02-19

5.  Risk of invasive candidiasis with prolonged duration of ICU stay: a systematic review and meta-analysis.

Authors:  Zhidan Zhang; Ran Zhu; Zhenggang Luan; Xiaochun Ma
Journal:  BMJ Open       Date:  2020-07-12       Impact factor: 2.692

6.  Risk Factors for Invasive Candida Infection in Critically Ill Patients: A Systematic Review and Meta-analysis.

Authors:  Daniel O Thomas-Rüddel; Peter Schlattmann; Mathias Pletz; Oliver Kurzai; Frank Bloos
Journal:  Chest       Date:  2021-10-18       Impact factor: 9.410

Review 7.  The Changing Landscape of Invasive Fungal Infections in ICUs: A Need for Risk Stratification to Better Target Antifungal Drugs and the Threat of Resistance.

Authors:  Julien Poissy; Anahita Rouzé; Marjorie Cornu; Saad Nseir; Boualem Sendid
Journal:  J Fungi (Basel)       Date:  2022-09-09

Review 8.  Deciphering the epidemiology of invasive candidiasis in the intensive care unit: is it possible?

Authors:  Vasiliki Soulountsi; Theodoros Schizodimos; Serafeim Chrysovalantis Kotoulas
Journal:  Infection       Date:  2021-06-16       Impact factor: 3.553

9.  Clinical predictive models of invasive Candida infection: A systematic literature review.

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

10.  Intensive Care Antifungal Stewardship Programme Based on T2Candida PCR and Candida Mannan Antigen: A Prospective Study.

Authors:  Jannik Helweg-Larsen; Morten Steensen; Finn Møller Pedersen; Pia Bredahl Jensen; Michael Perch; Kirsten Møller; Birthe Riis Olesen; Mathias Søderlund; Maiken Cavling Arendrup
Journal:  J Fungi (Basel)       Date:  2021-12-06
  10 in total

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