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AUtomated Risk Assessment for Stroke in Atrial Fibrillation (AURAS-AF) - an automated software system to promote anticoagulation and reduce stroke risk: study protocol for a cluster randomised…

Overview of attention for article published in Trials, November 2013
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Title
AUtomated Risk Assessment for Stroke in Atrial Fibrillation (AURAS-AF) - an automated software system to promote anticoagulation and reduce stroke risk: study protocol for a cluster randomised controlled trial
Published in
Trials, November 2013
DOI 10.1186/1745-6215-14-385
Pubmed ID
Authors

Tim A Holt, David A Fitzmaurice, Tom Marshall, Matthew Fay, Nadeem Qureshi, Andrew R H Dalton, F D Richard Hobbs, Daniel S Lasserson, Karen Kearley, Jenny Hislop, Jing Jin

Abstract

Patients with atrial fibrillation (AF) are at significantly increased risk of stroke. Oral anticoagulants (OACs) substantially reduce this risk, with gains seen across the spectrum of baseline risk. Despite the benefit to patients, OAC prescribing remains suboptimal in the United Kingdom (UK). We will investigate whether an automated software system, operating within primary care electronic medical records, can improve the management of AF by identifying patients eligible for OAC therapy and increasing uptake of this treatment.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 120 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Switzerland 1 <1%
South Africa 1 <1%
United Kingdom 1 <1%
Canada 1 <1%
Slovenia 1 <1%
United States 1 <1%
Unknown 114 95%

Demographic breakdown

Readers by professional status Count As %
Student > Master 26 22%
Researcher 19 16%
Student > Ph. D. Student 19 16%
Student > Postgraduate 7 6%
Student > Bachelor 6 5%
Other 23 19%
Unknown 20 17%
Readers by discipline Count As %
Medicine and Dentistry 51 43%
Pharmacology, Toxicology and Pharmaceutical Science 10 8%
Nursing and Health Professions 6 5%
Psychology 6 5%
Social Sciences 6 5%
Other 20 17%
Unknown 21 18%