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Diagnosis of obstructive coronary artery disease using computed tomography angiography in patients with stable chest pain depending on clinical probability and in clinically important subgroups: meta-a…

Overview of attention for article published in British Medical Journal, June 2019
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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 (98th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

news
9 news outlets
blogs
1 blog
twitter
73 tweeters
facebook
5 Facebook pages

Citations

dimensions_citation
14 Dimensions

Readers on

mendeley
75 Mendeley
Title
Diagnosis of obstructive coronary artery disease using computed tomography angiography in patients with stable chest pain depending on clinical probability and in clinically important subgroups: meta-analysis of individual patient data
Published in
British Medical Journal, June 2019
DOI 10.1136/bmj.l1945
Pubmed ID
Authors

Robert Haase, Peter Schlattmann, Pascal Gueret, Daniele Andreini, Gianluca Pontone, Hatem Alkadhi, Jörg Hausleiter, Mario J Garcia, Sebastian Leschka, Willem B Meijboom, Elke Zimmermann, Bernhard Gerber, U Joseph Schoepf, Abbas A Shabestari, Bjarne L Nørgaard, Matthijs F L Meijs, Akira Sato, Kristian A Ovrehus, Axel C P Diederichsen, Shona M M Jenkins, Juhani Knuuti, Ashraf Hamdan, Bjørn A Halvorsen, Vladimir Mendoza-Rodriguez, Carlos E Rochitte, Johannes Rixe, Yung Liang Wan, Christoph Langer, Nuno Bettencourt, Eugenio Martuscelli, Said Ghostine, Ronny R Buechel, Konstantin Nikolaou, Hans Mickley, Lin Yang, Zhaqoi Zhang, Marcus Y Chen, David A Halon, Matthias Rief, Kai Sun, Beatrice Hirt-Moch, Hiroyuki Niinuma, Roy P Marcus, Simone Muraglia, Réda Jakamy, Benjamin J Chow, Philipp A Kaufmann, Jean-Claude Tardif, Cesar Nomura, Klaus F Kofoed, Jean-Pierre Laissy, Armin Arbab-Zadeh, Kakuya Kitagawa, Roger Laham, Masahiro Jinzaki, John Hoe, Frank J Rybicki, Arthur Scholte, Narinder Paul, Swee Y Tan, Kunihiro Yoshioka, Robert Röhle, Georg M Schuetz, Sabine Schueler, Maria H Coenen, Viktoria Wieske, Stephan Achenbach, Matthew J Budoff, Michael Laule, David E Newby, Marc Dewey

Twitter Demographics

The data shown below were collected from the profiles of 73 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 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 75 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 19%
Student > Postgraduate 8 11%
Other 8 11%
Student > Master 7 9%
Student > Bachelor 6 8%
Other 15 20%
Unknown 17 23%
Readers by discipline Count As %
Medicine and Dentistry 38 51%
Neuroscience 2 3%
Nursing and Health Professions 2 3%
Psychology 2 3%
Physics and Astronomy 1 1%
Other 6 8%
Unknown 24 32%

Attention Score in Context

This research output has an Altmetric Attention Score of 115. 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 05 October 2020.
All research outputs
#191,071
of 16,336,603 outputs
Outputs from British Medical Journal
#2,896
of 50,492 outputs
Outputs of similar age
#5,356
of 270,817 outputs
Outputs of similar age from British Medical Journal
#97
of 798 outputs
Altmetric has tracked 16,336,603 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 50,492 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 36.4. This one has done particularly well, scoring higher than 94% 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 270,817 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 98% of its contemporaries.
We're also able to compare this research output to 798 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.