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β-D-glucan surveillance with preemptive anidulafungin for invasive candidiasis in intensive care unit patients: a randomized pilot study.
Abstract
<h4>Background</h4>Invasive candidiasis (IC) is a devastating disease. While prompt
antifungal therapy improves outcomes, empiric treatment based on the presence of fever
has little clinical impact. Β-D-Glucan (BDG) is a fungal cell wall component detectable
in the serum of patients with early invasive fungal infection (IFI). We evaluated
the utility of BDG surveillance as a guide for preemptive antifungal therapy in at-risk
intensive care unit (ICU) patients.<h4>Methods</h4>Patients admitted to the ICU for
≥ 3 days and expected to require at least 2 additional days of intensive care were
enrolled. Subjects were randomized in 3:1 fashion to receive twice weekly BDG surveillance
with preemptive anidulafungin in response to a positive test or empiric antifungal
treatment based on physician preference.<h4>Results</h4>Sixty-four subjects were enrolled,
with 1 proven and 5 probable cases of IC identified over a 2.5 year period. BDG levels
were higher in subjects with proven/probable IC as compared to those without an IFI
(117 pg/ml vs. 28 pg/ml; p<0.001). Optimal assay performance required 2 sequential
BDG determinations of ≥ 80 pg/ml to define a positive test (sensitivity 100%, specificity
75%, positive predictive value 30%, negative predictive value 100%). In all, 21 preemptive
and 5 empiric subjects received systemic antifungal therapy. Receipt of preemptive
antifungal treatment had a significant effect on BDG concentrations (p< 0.001). Preemptive
anidulafungin was safe and generally well tolerated with excellent outcome.<h4>Conclusions</h4>BDG
monitoring may be useful for identifying ICU patients at highest risk to develop an
IFI as well as for monitoring treatment response. Preemptive strategies based on fungal
biomarkers warrant further study.<h4>Trial registration</h4>Clinical Trials.gov NCT00672841.
Type
Journal articleSubject
Humansbeta-Glucans
Antifungal Agents
False Positive Reactions
Feasibility Studies
Pilot Projects
Predictive Value of Tests
Demography
Kinetics
Time Factors
Adult
Aged
Aged, 80 and over
Middle Aged
Intensive Care Units
Female
Male
Echinocandins
Young Adult
Candidiasis, Invasive
Anidulafungin
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https://hdl.handle.net/10161/26034Published Version (Please cite this version)
10.1371/journal.pone.0042282Publication Info
Hanson, Kimberly E; Pfeiffer, Christopher D; Lease, Erika D; Balch, Alfred H; Zaas,
Aimee K; Perfect, John R; & Alexander, Barbara D (2012). β-D-glucan surveillance with preemptive anidulafungin for invasive candidiasis in
intensive care unit patients: a randomized pilot study. PloS one, 7(8). pp. e42282. 10.1371/journal.pone.0042282. Retrieved from https://hdl.handle.net/10161/26034.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
Barbara Dudley Alexander
Professor of Medicine
Clinical research related to infectious complications of solid organ and bone marrow
transplantation, with a particular interest in the treatment and rapid diagnosis of
fungal disease. Training the next generation of Transplant Infectious Disease Physicians
is a special focus of mine as the Principal Investigator of our Interdisciplinary
T32 Training Program funded the NIH.
John Robert Perfect
James B. Duke Distinguished Professor of Medicine
Research in my laboratory focuses around several aspects of medical mycology. We
are investigating antifungal agents (new and old) in animal models of candida and
cryptococcal infections. We have examined clinical correlation of in vitro antifungal
susceptibility testing and with in vivo outcome. Our basic science project examines
the molecular pathogenesis of cryptococcal infections. We have developed a molecular
foundation for C. neoformans, including transformation systems, gene disr
Aimee Kirsch Zaas
Professor of Medicine
Medical education Genomic applications for diagnosis of infectious diseases Genomic
applications for prediction of infectious diseases
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