A comparison of host response strategies to distinguish bacterial and viral infection.
Abstract
<h4>Objectives</h4>Compare three host response strategies to distinguish bacterial
and viral etiologies of acute respiratory illness (ARI).<h4>Methods</h4>In this observational
cohort study, procalcitonin, a 3-protein panel (CRP, IP-10, TRAIL), and a host gene
expression mRNA panel were measured in 286 subjects with ARI from four emergency departments.
Multinomial logistic regression and leave-one-out cross validation were used to evaluate
the protein and mRNA tests.<h4>Results</h4>The mRNA panel performed better than alternative
strategies to identify bacterial infection: AUC 0.93 vs. 0.83 for the protein panel
and 0.84 for procalcitonin (P<0.02 for each comparison). This corresponded to a sensitivity
and specificity of 92% and 83% for the mRNA panel, 81% and 73% for the protein panel,
and 68% and 87% for procalcitonin, respectively. A model utilizing all three strategies
was the same as mRNA alone. For the diagnosis of viral infection, the AUC was 0.93
for mRNA and 0.84 for the protein panel (p<0.05). This corresponded to a sensitivity
and specificity of 89% and 82% for the mRNA panel, and 85% and 62% for the protein
panel, respectively.<h4>Conclusions</h4>A gene expression signature was the most accurate
host response strategy for classifying subjects with bacterial, viral, or non-infectious
ARI.
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https://hdl.handle.net/10161/24292Published Version (Please cite this version)
10.1371/journal.pone.0261385Publication Info
Ross, Melissa; Henao, Ricardo; Burke, Thomas W; Ko, Emily R; McClain, Micah T; Ginsburg,
Geoffrey S; ... Tsalik, Ephraim L (2021). A comparison of host response strategies to distinguish bacterial and viral infection.
PloS one, 16(12). pp. e0261385. 10.1371/journal.pone.0261385. Retrieved from https://hdl.handle.net/10161/24292.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
Geoffrey Steven Ginsburg
Adjunct Professor in the Department of Medicine
Dr. Geoffrey S. Ginsburg's research interests are in the development of novel paradigms
for developing and translating genomic information into medical practice and the integration
of personalized medicine into health care.
Ricardo Henao
Associate Professor in Biostatistics & Bioinformatics
Emily Ray Ko
Assistant Professor of Medicine
Clinical and translational research, COVID-19 therapeutics, clinical biomarkers for
infectious disease.
Micah Thomas McClain
Associate Professor of Medicine
Ephraim Tsalik
Adjunct Associate Professor in the Department of Medicine
My research at Duke has focused on understanding the dynamic between host and pathogen
so as to discover and develop host-response markers that can diagnose and predict
health and disease. This new and evolving approach to diagnosing illness has the
potential to significantly impact individual as well as public health considering
the rise of antibiotic resistance.
With any potential infectious disease diagnosis, it is difficult, if not impossible,
to determine at the time of pre
Christopher Wildrick Woods
Wolfgang Joklik Distinguished Professor of Global Health
1. Emerging Infections 2. Global Health 3. Epidemiology of infectious diseases
4. Clinical microbiology and diagnostics 5. Bioterrorism Preparedness 6. Surveillance
for communicable diseases 7. Antimicrobial resistance
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