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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.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Portugal 1 3%
Unknown 34 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 20%
Student > Bachelor 6 17%
Student > Ph. D. Student 5 14%
Other 5 14%
Unspecified 4 11%
Other 8 23%
Readers by discipline Count As %
Medicine and Dentistry 16 46%
Unspecified 8 23%
Agricultural and Biological Sciences 4 11%
Pharmacology, Toxicology and Pharmaceutical Science 2 6%
Immunology and Microbiology 2 6%
Other 3 9%

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
#6,299,529
of 8,302,052 outputs
Outputs from BMC Infectious Diseases
#2,730
of 3,706 outputs
Outputs of similar age
#179,103
of 252,348 outputs
Outputs of similar age from BMC Infectious Diseases
#139
of 205 outputs
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