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A Bayesian decision support tool for efficient dose individualization of warfarin in adults and children

Overview of attention for article published in BMC Medical Informatics and Decision Making, February 2015
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Citations

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Title
A Bayesian decision support tool for efficient dose individualization of warfarin in adults and children
Published in
BMC Medical Informatics and Decision Making, February 2015
DOI 10.1186/s12911-014-0128-0
Pubmed ID
Authors

Anna-Karin Hamberg, Jacob Hellman, Jonny Dahlberg, E Niclas Jonsson, Mia Wadelius

Abstract

Warfarin is the most widely prescribed anticoagulant for the prevention and treatment of thromboembolic events. Although highly effective, the use of warfarin is limited by a narrow therapeutic range combined with a more than ten-fold difference in the dose required for adequate anticoagulation in adults. An optimal dose that leads to a favourable balance between the wanted antithrombotic effect and the risk of bleeding as measured by the prothrombin time International Normalised Ratio (INR) must be found for each patient. A model describing the time-course of the INR response can be used to aid dose selection before starting therapy (a priori dose prediction) and after therapy has been initiated (a posteriori dose revision).

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Australia 1 2%
Unknown 50 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 24%
Student > Ph. D. Student 8 16%
Student > Master 7 14%
Student > Doctoral Student 5 10%
Student > Bachelor 4 8%
Other 9 18%
Unknown 6 12%
Readers by discipline Count As %
Medicine and Dentistry 13 25%
Pharmacology, Toxicology and Pharmaceutical Science 10 20%
Biochemistry, Genetics and Molecular Biology 4 8%
Computer Science 3 6%
Agricultural and Biological Sciences 3 6%
Other 8 16%
Unknown 10 20%
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 09 February 2015.
All research outputs
#18,397,250
of 22,787,797 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,570
of 1,986 outputs
Outputs of similar age
#256,873
of 352,561 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#21
of 24 outputs
Altmetric has tracked 22,787,797 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,986 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 9th percentile – i.e., 9% of its peers scored the same or lower than it.
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 352,561 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.