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Evaluation of algorithms for registry-based detection of acute myocardial infarction following percutaneous coronary intervention

Overview of attention for article published in Clinical Epidemiology, October 2016
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Title
Evaluation of algorithms for registry-based detection of acute myocardial infarction following percutaneous coronary intervention
Published in
Clinical Epidemiology, October 2016
DOI 10.2147/clep.s108906
Pubmed ID
Authors

Gro Egholm, Morten Madsen, Troels Thim, Morten Schmidt, Evald Høj Christiansen, Hans Erik Bøtker, Michael Maeng

Abstract

Registry-based monitoring of the safety and efficacy of interventions in patients with ischemic heart disease requires validated algorithms. We aimed to evaluate algorithms to identify acute myocardial infarction (AMI) in the Danish National Patient Registry following percutaneous coronary intervention (PCI). Patients enrolled in clinical drug-eluting stent studies at the Department of Cardiology, Aarhus University Hospital, Denmark, from January 2006 to August 2012 were included. These patients were evaluated for ischemic events, including AMI, during follow-up using an end point committee adjudication of AMI as reference standard. Of 5,719 included patients, 285 patients suffered AMI within a mean follow-up time of 3 years after stent implantation. An AMI discharge diagnosis (primary or secondary) from any acute or elective admission had a sensitivity of 95%, a specificity of 93%, and a positive predictive value of 42%. Restriction to acute admissions decreased the sensitivity to 94% but increased the specificity to 98% and the positive predictive value to 73%. Further restriction to include only AMI as primary diagnosis from acute admissions decreased the sensitivity further to 82%, but increased the specificity to 99% and the positive predictive value to 81%. Restriction to patients admitted to hospitals with a coronary angiography catheterization laboratory increased the positive predictive value to 87%. Algorithms utilizing additional information from the Danish National Patient Registry yield different sensitivities, specificities, and predictive values in registry-based detection of AMI following PCI. We were able to identify AMI following PCI with moderate-to-high validity. However, the choice of algorithm will depend on the specific study purpose.

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Geographical breakdown

Country Count As %
Unknown 20 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 20%
Student > Bachelor 2 10%
Researcher 2 10%
Student > Master 2 10%
Other 1 5%
Other 3 15%
Unknown 6 30%
Readers by discipline Count As %
Medicine and Dentistry 10 50%
Pharmacology, Toxicology and Pharmaceutical Science 1 5%
Agricultural and Biological Sciences 1 5%
Nursing and Health Professions 1 5%
Neuroscience 1 5%
Other 1 5%
Unknown 5 25%
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 19 October 2016.
All research outputs
#20,655,488
of 25,371,288 outputs
Outputs from Clinical Epidemiology
#639
of 793 outputs
Outputs of similar age
#257,455
of 332,555 outputs
Outputs of similar age from Clinical Epidemiology
#22
of 30 outputs
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