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Translational and emerging clinical applications of metabolomics in cardiovascular disease diagnosis and treatment

Overview of attention for article published in European Journal of Preventive Cardiology, July 2016
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Article details
Title
Translational and emerging clinical applications of metabolomics in cardiovascular disease diagnosis and treatment
Published in
European Journal of Preventive Cardiology, July 2016
DOI 10.1177/2047487316645469
Pubmed ID
Authors
Abstract

Numerous molecular screening strategies have recently been developed to measure the chemical diversity of a population's biofluids with the ultimate aim to provide clinicians, medical scientists and epidemiologists with a clearer picture of the presence and severity of cardiovascular disease; prognosis; and response to treatment. Current cardiology practice integrates clinical history and examination with state-of-the-art imaging, invasive measures, and electrical interrogation. Biomarkers in common clinical use are relatively limited to troponin and brain natriuretic peptide, dependent on damage to heart muscle, or myocyte 'stretch' respectively. Although they have been recently applied to risk stratification in asymptomatic individuals at higher risk, the development of markers capable of detecting earlier phases of disease development would facilitate targeted strategies to prevent pathological complications in the general community. Metabolomics is the systematic study of small molecules in biological fluids. Profiling strategies aim to comprehensively measure and quantify such biomarkers in a fast, cost-effective and clinically informative manner. Techniques tend to be applied in an unbiased fashion, with advanced statistical methods allowing for identification of signature profiles in particular cohorts. In this manner, metabolomics has the potential to identify new pathophysiological pathways, and thus therapeutic targets, as well as assist in improved risk-stratification and personalized cardiovascular medicine. The latter has great potential in the primary and secondary cardiovascular disease prevention settings, integrating known and as yet unidentified host and environmental factors. The current review discusses applications of metabolomic techniques relevant to both the research and the clinical cardiologist.

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X Demographics

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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 66 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Netherlands 1 2%
Spain 1 2%
Unknown 64 97%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 10 15%
Student > Master 10 15%
Researcher 10 15%
Student > Bachelor 5 8%
Professor > Associate Professor 5 8%
Other 13 20%
Unknown 13 20%
Readers by discipline
Readers by discipline Count As %
Medicine and Dentistry 15 23%
Biochemistry, Genetics and Molecular Biology 14 21%
Agricultural and Biological Sciences 4 6%
Neuroscience 3 5%
Chemistry 3 5%
Other 10 15%
Unknown 17 26%
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 23 April 2016.
All research outputs
#21,540,108
of 27,265,018 outputs
Outputs from European Journal of Preventive Cardiology
#2,709
of 3,175 outputs
Outputs of similar age
#238,591
of 330,995 outputs
Outputs of similar age from European Journal of Preventive Cardiology
#40
of 54 outputs
Altmetric has tracked 27,265,018 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,175 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 31.5. This one is in the 13th percentile – i.e., 13% 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 330,995 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 54 others from the same source and published within six weeks on either side of this one. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.