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Predicting the risk of bleeding during dual antiplatelet therapy after acute coronary syndromes

Overview of attention for article published in Heart, April 2017
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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 (85th percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

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1 news outlet
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9 X users
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1 Facebook page

Citations

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36 Dimensions

Readers on

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136 Mendeley
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Title
Predicting the risk of bleeding during dual antiplatelet therapy after acute coronary syndromes
Published in
Heart, April 2017
DOI 10.1136/heartjnl-2016-310090
Pubmed ID
Authors

Joakim Alfredsson, Benjamin Neely, Megan L Neely, Deepak L Bhatt, Shaun G Goodman, Pierluigi Tricoci, Kenneth W Mahaffey, Jan H Cornel, Harvey D White, Keith AA Fox, Dorairaj Prabhakaran, Kenneth J Winters, Paul W Armstrong, E Magnus Ohman, Matthew T Roe

Abstract

Dual antiplatelet therapy (DAPT) with aspirin + a P2Y12 inhibitor is recommended for at least 12 months for patients with acute coronary syndrome (ACS), with shorter durations considered for patients with increased bleeding risk. However, there are no decision support tools available to predict an individual patient's bleeding risk during DAPT treatment in the post-ACS setting. To develop a longitudinal bleeding risk prediction model, we analysed 9240 patients with unstable angina/non-ST segment elevation myocardial infarction (NSTEMI) from the Targeted Platelet Inhibition to Clarify the Optimal Strategy to Medically Manage Acute Coronary Syndromes (TRILOGY ACS) trial, who were managed without revascularisation and treated with DAPT for a median of 14.8 months. We identified 10 significant baseline predictors of non-coronary artery bypass grafting (CABG)-related Global Use of Strategies to Open Occluded Arteries (GUSTO) severe/life-threatening/moderate bleeding: age, sex, weight, NSTEMI (vs unstable angina), angiography performed before randomisation, prior peptic ulcer disease, creatinine, systolic blood pressure, haemoglobin and treatment with beta-blocker. The five significant baseline predictors of Thrombolysis In Myocardial Infarction (TIMI) major or minor bleeding included age, sex, angiography performed before randomisation, creatinine and haemoglobin. The models showed good predictive accuracy with Therneau's C-indices: 0.78 (SE=0.024) for the GUSTO model and 0.67 (SE=0.023) for the TIMI model. Internal validation with bootstrapping gave similar C-indices of 0.77 and 0.65, respectively. External validation demonstrated an attenuated C-index for the GUSTO model (0.69) but not the TIMI model (0.68). Longitudinal bleeding risks during treatment with DAPT in patients with ACS can be reliably predicted using selected baseline characteristics. The TRILOGY ACS bleeding models can inform risk-benefit considerations regarding the duration of DAPT following ACS. ClinicalTrials.gov identifier: https://clinicaltrials.gov/ct2/show/NCT00699998.

X Demographics

X Demographics

The data shown below were collected from the profiles of 9 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 136 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 136 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 21 15%
Student > Bachelor 17 13%
Other 15 11%
Researcher 15 11%
Student > Ph. D. Student 10 7%
Other 23 17%
Unknown 35 26%
Readers by discipline Count As %
Medicine and Dentistry 58 43%
Pharmacology, Toxicology and Pharmaceutical Science 10 7%
Nursing and Health Professions 5 4%
Biochemistry, Genetics and Molecular Biology 3 2%
Sports and Recreations 2 1%
Other 7 5%
Unknown 51 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 26 September 2017.
All research outputs
#2,300,490
of 23,989,841 outputs
Outputs from Heart
#1,249
of 5,915 outputs
Outputs of similar age
#43,881
of 312,589 outputs
Outputs of similar age from Heart
#40
of 118 outputs
Altmetric has tracked 23,989,841 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 5,915 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 21.2. This one has done well, scoring higher than 78% 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 312,589 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 118 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.