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Discriminating Bacterial and Viral Infection Using a Rapid Host Gene Expression Test.

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Date
2021-10
Authors
Tsalik, Ephraim L
Henao, Ricardo
Montgomery, Jesse L
Nawrocki, Jeff W
Aydin, Mert
Lydon, Emily C
Ko, Emily R
Petzold, Elizabeth
Nicholson, Bradly P
Cairns, Charles B
Glickman, Seth W
Quackenbush, Eugenia
Kingsmore, Stephen F
Jaehne, Anja K
Rivers, Emanuel P
Langley, Raymond J
Fowler, Vance G
McClain, Micah T
Crisp, Robert J
Ginsburg, Geoffrey S
Burke, Thomas W
Hemmert, Andrew C
Woods, Christopher W
Antibacterial Resistance Leadership Group
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Abstract
<h4>Objectives</h4>Host gene expression signatures discriminate bacterial and viral infection but have not been translated to a clinical test platform. This study enrolled an independent cohort of patients to describe and validate a first-in-class host response bacterial/viral test.<h4>Design</h4>Subjects were recruited from 2006 to 2016. Enrollment blood samples were collected in an RNA preservative and banked for later testing. The reference standard was an expert panel clinical adjudication, which was blinded to gene expression and procalcitonin results.<h4>Setting</h4>Four U.S. emergency departments.<h4>Patients</h4>Six-hundred twenty-three subjects with acute respiratory illness or suspected sepsis.<h4>Interventions</h4>Forty-five-transcript signature measured on the BioFire FilmArray System (BioFire Diagnostics, Salt Lake City, UT) in ~45 minutes.<h4>Measurements and main results</h4>Host response bacterial/viral test performance characteristics were evaluated in 623 participants (mean age 46 yr; 45% male) with bacterial infection, viral infection, coinfection, or noninfectious illness. Performance of the host response bacterial/viral test was compared with procalcitonin. The test provided independent probabilities of bacterial and viral infection in ~45 minutes. In the 213-subject training cohort, the host response bacterial/viral test had an area under the curve for bacterial infection of 0.90 (95% CI, 0.84-0.94) and 0.92 (95% CI, 0.87-0.95) for viral infection. Independent validation in 209 subjects revealed similar performance with an area under the curve of 0.85 (95% CI, 0.78-0.90) for bacterial infection and 0.91 (95% CI, 0.85-0.94) for viral infection. The test had 80.1% (95% CI, 73.7-85.4%) average weighted accuracy for bacterial infection and 86.8% (95% CI, 81.8-90.8%) for viral infection in this validation cohort. This was significantly better than 68.7% (95% CI, 62.4-75.4%) observed for procalcitonin (p < 0.001). An additional cohort of 201 subjects with indeterminate phenotypes (coinfection or microbiology-negative infections) revealed similar performance.<h4>Conclusions</h4>The host response bacterial/viral measured using the BioFire System rapidly and accurately discriminated bacterial and viral infection better than procalcitonin, which can help support more appropriate antibiotic use.
Type
Journal article
Subject
Antibacterial Resistance Leadership Group
Humans
Bacterial Infections
Virus Diseases
Clinical Laboratory Techniques
Adult
Middle Aged
Emergency Service, Hospital
Female
Male
Transcriptome
Biomarkers
Permalink
https://hdl.handle.net/10161/23936
Published Version (Please cite this version)
10.1097/ccm.0000000000005085
Publication Info
Tsalik, Ephraim L; Henao, Ricardo; Montgomery, Jesse L; Nawrocki, Jeff W; Aydin, Mert; Lydon, Emily C; ... Antibacterial Resistance Leadership Group (2021). Discriminating Bacterial and Viral Infection Using a Rapid Host Gene Expression Test. Critical care medicine, 49(10). pp. 1651-1663. 10.1097/ccm.0000000000005085. Retrieved from https://hdl.handle.net/10161/23936.
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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Scholars@Duke

Burke

Thomas Burke

Manager, Systems Project
Fowler

Vance Garrison Fowler Jr.

Florence McAlister Distinguished Professor of Medicine
Determinants of Outcome in Patients with Staphylococcus aureus Bacteremia Antibacterial ResistancePathogenesis of Bacterial Infections Tropical medicine/International Health
Ginsburg

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.
Henao

Ricardo Henao

Associate Professor in Biostatistics & Bioinformatics
Ko

Emily Ray Ko

Assistant Professor of Medicine
Clinical and translational research, COVID-19 therapeutics, clinical biomarkers for infectious disease.
McClain

Micah Thomas McClain

Associate Professor of Medicine
Tsalik

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
Woods

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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