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A Path to Implement Precision Child Health Cardiovascular Medicine

Overview of attention for article published in Frontiers in Cardiovascular Medicine, June 2017
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Title
A Path to Implement Precision Child Health Cardiovascular Medicine
Published in
Frontiers in Cardiovascular Medicine, June 2017
DOI 10.3389/fcvm.2017.00036
Pubmed ID
Authors

Marlin Touma, Brian Reemtsen, Nancy Halnon, Juan Alejos, J. Paul Finn, Stanley F. Nelson, Yibin Wang

Abstract

Congenital heart defects (CHDs) affect approximately 1% of live births and are a major source of childhood morbidity and mortality even in countries with advanced healthcare systems. Along with phenotypic heterogeneity, the underlying etiology of CHDs is multifactorial, involving genetic, epigenetic, and/or environmental contributors. Clear dissection of the underlying mechanism is a powerful step to establish individualized therapies. However, the majority of CHDs are yet to be clearly diagnosed for the underlying genetic and environmental factors, and even less with effective therapies. Although the survival rate for CHDs is steadily improving, there is still a significant unmet need for refining diagnostic precision and establishing targeted therapies to optimize life quality and to minimize future complications. In particular, proper identification of disease associated genetic variants in humans has been challenging, and this greatly impedes our ability to delineate gene-environment interactions that contribute to the pathogenesis of CHDs. Implementing a systematic multileveled approach can establish a continuum from phenotypic characterization in the clinic to molecular dissection using combined next-generation sequencing platforms and validation studies in suitable models at the bench. Key elements necessary to advance the field are: first, proper delineation of the phenotypic spectrum of CHDs; second, defining the molecular genotype/phenotype by combining whole-exome sequencing and transcriptome analysis; third, integration of phenotypic, genotypic, and molecular datasets to identify molecular network contributing to CHDs; fourth, generation of relevant disease models and multileveled experimental investigations. In order to achieve all these goals, access to high-quality biological specimens from well-defined patient cohorts is a crucial step. Therefore, establishing a CHD BioCore is an essential infrastructure and a critical step on the path toward precision child health cardiovascular medicine.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 20 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 40%
Other 2 10%
Student > Postgraduate 2 10%
Student > Master 2 10%
Student > Bachelor 1 5%
Other 1 5%
Unknown 4 20%
Readers by discipline Count As %
Medicine and Dentistry 6 30%
Biochemistry, Genetics and Molecular Biology 5 25%
Agricultural and Biological Sciences 3 15%
Business, Management and Accounting 1 5%
Pharmacology, Toxicology and Pharmaceutical Science 1 5%
Other 1 5%
Unknown 3 15%
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 18 June 2017.
All research outputs
#15,462,982
of 22,977,819 outputs
Outputs from Frontiers in Cardiovascular Medicine
#2,592
of 6,875 outputs
Outputs of similar age
#198,874
of 316,526 outputs
Outputs of similar age from Frontiers in Cardiovascular Medicine
#13
of 22 outputs
Altmetric has tracked 22,977,819 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,875 research outputs from this source. They receive a mean Attention Score of 4.2. This one has gotten more attention than average, scoring higher than 59% of its peers.
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 316,526 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 22 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.