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Genomic Risk Prediction of Coronary Artery Disease in 480,000 Adults Implications for Primary Prevention

Overview of attention for article published in JACC, October 2018
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Citations

dimensions_citation
594 Dimensions

Readers on

mendeley
550 Mendeley
citeulike
2 CiteULike
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Title
Genomic Risk Prediction of Coronary Artery Disease in 480,000 Adults Implications for Primary Prevention
Published in
JACC, October 2018
DOI 10.1016/j.jacc.2018.07.079
Pubmed ID
Authors

Michael Inouye, Gad Abraham, Christopher P. Nelson, Angela M. Wood, Michael J. Sweeting, Frank Dudbridge, Florence Y. Lai, Stephen Kaptoge, Marta Brozynska, Tingting Wang, Shu Ye, Thomas R. Webb, Martin K. Rutter, Ioanna Tzoulaki, Riyaz S. Patel, Ruth J.F. Loos, Bernard Keavney, Harry Hemingway, John Thompson, Hugh Watkins, Panos Deloukas, Emanuele Di Angelantonio, Adam S. Butterworth, John Danesh, Nilesh J. Samani, Biobank CardioMetabolic Consortium CHD Working Group

X Demographics

X Demographics

The data shown below were collected from the profiles of 294 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 550 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 550 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 94 17%
Researcher 91 17%
Student > Master 49 9%
Student > Bachelor 43 8%
Student > Doctoral Student 32 6%
Other 99 18%
Unknown 142 26%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 116 21%
Medicine and Dentistry 116 21%
Agricultural and Biological Sciences 41 7%
Computer Science 17 3%
Psychology 12 2%
Other 79 14%
Unknown 169 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 356. 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 03 May 2024.
All research outputs
#92,254
of 25,840,929 outputs
Outputs from JACC
#211
of 16,965 outputs
Outputs of similar age
#1,793
of 355,951 outputs
Outputs of similar age from JACC
#8
of 242 outputs
Altmetric has tracked 25,840,929 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 16,965 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 30.1. This one has done particularly well, scoring higher than 98% 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 355,951 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 99% of its contemporaries.
We're also able to compare this research output to 242 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.