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Urine metabolomic profiling of children with respiratory tract infections in the emergency department: a pilot study

Overview of attention for article published in BMC Infectious Diseases, August 2016
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Title
Urine metabolomic profiling of children with respiratory tract infections in the emergency department: a pilot study
Published in
BMC Infectious Diseases, August 2016
DOI 10.1186/s12879-016-1709-6
Pubmed ID
Authors

Darryl J. Adamko, Erik Saude, Matthew Bear, Shana Regush, Joan L. Robinson

Abstract

Clinicians lack objective tests to help determine the severity of bronchiolitis or to distinguish a viral from bacterial causes of respiratory distress. We hypothesized that children with respiratory syncytial virus (RSV) infection would have a different metabolomic profile compared to those with bacterial infection or healthy controls, and this might also vary with bronchiolitis severity. Clinical information and urine-based metabolomic data were collected from healthy age-matched children (n = 37) and those admitted to hospital with a proven infection (RSV n = 55; Non-RSV viral n = 16; bacterial n = 24). Nuclear magnetic resonance (NMR) measured 86 metabolites per urine sample. Partial least squares discriminant analysis (PLS-DA) was performed to create models of separation. Using a combination of metabolites, a strong PLS-DA model (R2 = 0.86, Q2 = 0.76) was created differentiating healthy children from those with RSV infection. This model had over 90 % accuracy in classifying blinded infants with similar illness severity. Two other models differentiated length of hospitalization and viral versus bacterial infection. While the sample sizes remain small, this is the first report suggesting that metabolomic analysis of urine samples has the potential to become a diagnostic aid. Future studies with larger sample sizes are required to validate the utility of metabolomics in pediatric patients with respiratory distress.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Portugal 1 2%
Unknown 62 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 22%
Student > Bachelor 10 16%
Student > Ph. D. Student 9 14%
Student > Master 5 8%
Other 5 8%
Other 7 11%
Unknown 13 21%
Readers by discipline Count As %
Medicine and Dentistry 21 33%
Biochemistry, Genetics and Molecular Biology 6 10%
Agricultural and Biological Sciences 5 8%
Nursing and Health Professions 3 5%
Chemistry 3 5%
Other 6 10%
Unknown 19 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 30 August 2016.
All research outputs
#18,468,369
of 22,884,315 outputs
Outputs from BMC Infectious Diseases
#5,617
of 7,690 outputs
Outputs of similar age
#263,392
of 343,744 outputs
Outputs of similar age from BMC Infectious Diseases
#139
of 202 outputs
Altmetric has tracked 22,884,315 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
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