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Exploring the interaction between SNP genotype and postmenopausal hormone therapy effects on stroke risk

Overview of attention for article published in Genome Medicine, July 2012
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (91st percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

Mentioned by

blogs
1 blog
twitter
13 tweeters

Citations

dimensions_citation
7 Dimensions

Readers on

mendeley
25 Mendeley
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Title
Exploring the interaction between SNP genotype and postmenopausal hormone therapy effects on stroke risk
Published in
Genome Medicine, July 2012
DOI 10.1186/gm358
Pubmed ID
Authors

Ying Huang, Dennis G Ballinger, Renee Stokowski, Erica Beilharz, Jennifer G Robinson, Simin Liu, Randal D Robinson, Victor W Henderson, Jacques E Rossouw, Ross L Prentice, Huang Y, Ballinger DG, Stokowski R, Beilharz E, Robinson JG, Liu S, Robinson R, Henderson VW, Rossouw JE, Prentice RL

Abstract

Genome-wide association studies have identified several genomic regions that are associated with stroke risk, but these provide an explanation for only a small fraction of familial stroke aggregation. Genotype by environment interactions may contribute further to such an explanation. The Women's Health Initiative (WHI) clinical trial found increased stroke risk with postmenopausal hormone therapy (HT) and provides an efficient setting for evaluating genotype-HT interaction on stroke risk.

Twitter Demographics

The data shown below were collected from the profiles of 13 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 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 4%
Romania 1 4%
Unknown 23 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 16%
Student > Ph. D. Student 4 16%
Professor > Associate Professor 3 12%
Other 2 8%
Student > Bachelor 2 8%
Other 5 20%
Unknown 5 20%
Readers by discipline Count As %
Medicine and Dentistry 8 32%
Agricultural and Biological Sciences 4 16%
Biochemistry, Genetics and Molecular Biology 2 8%
Sports and Recreations 1 4%
Computer Science 1 4%
Other 0 0%
Unknown 9 36%

Attention Score in Context

This research output has an Altmetric Attention Score of 15. 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 22 September 2012.
All research outputs
#1,986,958
of 22,054,848 outputs
Outputs from Genome Medicine
#459
of 1,398 outputs
Outputs of similar age
#9,435
of 108,751 outputs
Outputs of similar age from Genome Medicine
#3
of 11 outputs
Altmetric has tracked 22,054,848 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,398 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.5. This one has gotten more attention than average, scoring higher than 67% 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 108,751 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.