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Genetic Evaluation and Use of Chromosome Microarray in Patients with Isolated Heart Defects: Benefits and Challenges of a New Model in Cardiovascular Care

Overview of attention for article published in Frontiers in Cardiovascular Medicine, June 2016
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Title
Genetic Evaluation and Use of Chromosome Microarray in Patients with Isolated Heart Defects: Benefits and Challenges of a New Model in Cardiovascular Care
Published in
Frontiers in Cardiovascular Medicine, June 2016
DOI 10.3389/fcvm.2016.00019
Pubmed ID
Authors

Benjamin M. Helm, Samantha L. Freeze

Abstract

Congenital heart defects (CHDs) are common birth defects and result in significant morbidity and global economic impact. Genetic factors play a role in most CHDs; however, identification of these factors has been historically slow due to technological limitations and incomplete understanding of the impact of human genomic variation on normal and abnormal cardiovascular development. The advent of chromosome microarray (CMA) brought tremendous gains in identifying chromosome abnormalities in a variety of human disorders and is now considered part of a standard evaluation for individuals with multiple congenital anomalies and/or neurodevelopmental disorders. Several studies investigating use of CMA found that this technology can identify pathogenic copy-number variations (CNVs) in up to 15-20% of patients with CHDs with other congenital anomalies. However, there have been fewer studies exploring the use of CMA for patients with isolated CHDs. Recent studies have shown that the diagnostic yield of CMA in individuals with seemingly isolated CHD is lower than in individuals with CHDs and additional anomalies. Nevertheless, positive CMA testing in this group supports chromosome variation as one mechanism underlying the development of isolated, non-syndromic CHD - either as a causative or risk-influencing genetic factor. CMA has also identified novel genomic variation in CHDs, shedding light on candidate genes and pathways involved in cardiac development and malformations. Additional studies are needed to further address this issue. Early genetic diagnosis can enhance the medical management of patients and potentially provide crucial information about recurrence. This information is critical for genetic counseling of patients and family members. In this review, we review CMA for the non-genetics cardiology provider, offer a summary of CNV in isolated CHDs, and advocate for the use of CMA as part of the cardiovascular genetics evaluation of patients with isolated CHDs. We also provide perspective regarding the benefits and challenges that lie ahead for this model in the clinical setting.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status Count As %
Other 5 15%
Student > Ph. D. Student 5 15%
Researcher 3 9%
Student > Bachelor 3 9%
Student > Doctoral Student 2 6%
Other 8 24%
Unknown 8 24%
Readers by discipline Count As %
Medicine and Dentistry 13 38%
Biochemistry, Genetics and Molecular Biology 6 18%
Nursing and Health Professions 2 6%
Agricultural and Biological Sciences 2 6%
Unspecified 1 3%
Other 1 3%
Unknown 9 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 04 August 2016.
All research outputs
#15,379,760
of 22,880,230 outputs
Outputs from Frontiers in Cardiovascular Medicine
#2,571
of 6,783 outputs
Outputs of similar age
#222,553
of 352,718 outputs
Outputs of similar age from Frontiers in Cardiovascular Medicine
#8
of 13 outputs
Altmetric has tracked 22,880,230 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 6,783 research outputs from this source. They receive a mean Attention Score of 4.1. This one has gotten more attention than average, scoring higher than 58% 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 352,718 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 13 others from the same source and published within six weeks on either side of this one. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.