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Development of metabolic and inflammatory mediator biomarker phenotyping for early diagnosis and triage of pediatric sepsis

Overview of attention for article published in Critical Care, December 2015
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  • Good Attention Score compared to outputs of the same age (74th percentile)

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Title
Development of metabolic and inflammatory mediator biomarker phenotyping for early diagnosis and triage of pediatric sepsis
Published in
Critical Care, December 2015
DOI 10.1186/s13054-015-1026-2
Pubmed ID
Authors

Beata Mickiewicz, Graham C. Thompson, Jaime Blackwood, Craig N. Jenne, Brent W. Winston, Hans J. Vogel, Ari R. Joffe

Abstract

The first steps in goal-directed therapy for sepsis are early diagnosis followed by appropriate triage. These steps are usually left to the physician's judgment, as there is no accepted biomarker available. We aimed to determine biomarker phenotypes that differentiate children with sepsis who require intensive care from those who do not. We conducted a prospective, observational nested cohort study at two pediatric intensive care units (PICUs) and one pediatric emergency department (ED). Children ages 2-17 years presenting to the PICU or ED with sepsis or presenting for procedural sedation to the ED were enrolled. We used the judgment of regional pediatric ED and PICU attending physicians as the standard to determine triage location (PICU or ED). We performed metabolic and inflammatory protein mediator profiling with serum and plasma samples, respectively, collected upon presentation, followed by multivariate statistical analysis. Ninety-four PICU sepsis, 81 ED sepsis, and 63 ED control patients were included. Metabolomic profiling revealed clear separation of groups, differentiating PICU sepsis from ED sepsis with accuracy of 0.89, area under the receiver operating characteristic curve (AUROC) of 0.96 (standard deviation [SD] 0.01), and predictive ability (Q (2)) of 0.60. Protein mediator profiling also showed clear separation of the groups, differentiating PICU sepsis from ED sepsis with accuracy of 0.78 and AUROC of 0.88 (SD 0.03). Combining metabolomic and protein mediator profiling improved the model (Q (2) =0.62), differentiating PICU sepsis from ED sepsis with accuracy of 0.87 and AUROC of 0.95 (SD 0.01). Separation of PICU sepsis or ED sepsis from ED controls was even more accurate. Prespecified age subgroups (2-5 years old and 6-17 years old) improved model accuracy minimally. Seventeen metabolites or protein mediators accounted for separation of PICU sepsis and ED sepsis with 95 % confidence. In children ages 2-17 years, combining metabolomic and inflammatory protein mediator profiling early after presentation may differentiate children with sepsis requiring care in a PICU from children with or without sepsis safely cared for outside a PICU. This may aid in making triage decisions, particularly in an ED without pediatric expertise. This finding requires validation in an independent cohort.

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The data shown below were collected from the profiles of 10 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 118 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Unknown 117 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 13%
Student > Master 14 12%
Other 13 11%
Student > Ph. D. Student 13 11%
Student > Doctoral Student 7 6%
Other 27 23%
Unknown 29 25%
Readers by discipline Count As %
Medicine and Dentistry 46 39%
Agricultural and Biological Sciences 11 9%
Biochemistry, Genetics and Molecular Biology 5 4%
Nursing and Health Professions 5 4%
Immunology and Microbiology 4 3%
Other 14 12%
Unknown 33 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 16 September 2015.
All research outputs
#6,930,354
of 25,374,917 outputs
Outputs from Critical Care
#3,868
of 6,554 outputs
Outputs of similar age
#98,494
of 395,418 outputs
Outputs of similar age from Critical Care
#333
of 466 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
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 40th percentile – i.e., 40% 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 395,418 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 466 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.