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Interleukin-27 is a novel candidate diagnostic biomarker for bacterial infection in critically ill children

Overview of attention for article published in Critical Care, October 2012
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

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6 X users
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1 patent
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1 Facebook page

Citations

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86 Dimensions

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69 Mendeley
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Title
Interleukin-27 is a novel candidate diagnostic biomarker for bacterial infection in critically ill children
Published in
Critical Care, October 2012
DOI 10.1186/cc11847
Pubmed ID
Authors

Hector R Wong, Natalie Z Cvijanovich, Mark Hall, Geoffrey L Allen, Neal J Thomas, Robert J Freishtat, Nick Anas, Keith Meyer, Paul A Checchia, Richard Lin, Michael T Bigham, Anita Sen, Jeffrey Nowak, Michael Quasney, Jared W Henricksen, Arun Chopra, Sharon Banschbach, Eileen Beckman, Kelli Harmon, Patrick Lahni, Thomas P Shanley

Abstract

ABSTRACT: INTRODUCTION: Differentiating between sterile inflammation and bacterial infection in critically ill patients with fever and other signs of the systemic inflammatory response syndrome (SIRS) remains a clinical challenge. The objective of our study was to mine an existing genome-wide expression database for the discovery of candidate diagnostic biomarkers to predict the presence of bacterial infection in critically ill children. METHODS: Genome-wide expression data were compared between patients with SIRS having negative bacterial cultures (n = 21) and patients with sepsis having positive bacterial cultures (n = 60). Differentially expressed genes were subjected to a leave-one-out cross-validation (LOOCV) procedure to predict SIRS or sepsis classes. Serum concentrations of interleukin-27 (IL-27) and procalcitonin (PCT) were compared between 101 patients with SIRS and 130 patients with sepsis. All data represent the first 24 hours of meeting criteria for either SIRS or sepsis. RESULTS: Two hundred twenty one gene probes were differentially regulated between patients with SIRS and patients with sepsis. The LOOCV procedure correctly predicted 86% of the SIRS and sepsis classes, and Epstein-Barr virus-induced gene 3 (EBI3) had the highest predictive strength. Computer-assisted image analyses of gene-expression mosaics were able to predict infection with a specificity of 90% and a positive predictive value of 94%. Because EBI3 is a subunit of the heterodimeric cytokine, IL-27, we tested the ability of serum IL-27 protein concentrations to predict infection. At a cut-point value of ≥5 ng/ml, serum IL-27 protein concentrations predicted infection with a specificity and a positive predictive value of >90%, and the overall performance of IL-27 was generally better than that of PCT. A decision tree combining IL-27 and PCT improved overall predictive capacity compared with that of either biomarker alone. CONCLUSIONS: Genome-wide expression analysis has provided the foundation for the identification of IL-27 as a novel candidate diagnostic biomarker for predicting bacterial infection in critically ill children. Additional studies will be required to test further the diagnostic performance of IL-27.The microarray data reported in this article have been deposited in the Gene Expression Omnibus under accession number GSE4607.

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X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
France 1 1%
Norway 1 1%
Unknown 66 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 19%
Student > Master 8 12%
Student > Ph. D. Student 7 10%
Student > Postgraduate 6 9%
Professor 5 7%
Other 14 20%
Unknown 16 23%
Readers by discipline Count As %
Medicine and Dentistry 29 42%
Agricultural and Biological Sciences 13 19%
Biochemistry, Genetics and Molecular Biology 5 7%
Nursing and Health Professions 2 3%
Pharmacology, Toxicology and Pharmaceutical Science 1 1%
Other 2 3%
Unknown 17 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 May 2016.
All research outputs
#5,188,039
of 25,374,647 outputs
Outputs from Critical Care
#3,375
of 6,554 outputs
Outputs of similar age
#38,426
of 202,212 outputs
Outputs of similar age from Critical Care
#28
of 128 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,554 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.8. This one is in the 48th percentile – i.e., 48% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 202,212 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 80% of its contemporaries.
We're also able to compare this research output to 128 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.