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Discrete Event Simulation Model of Sudden Cardiac Death Predicts High Impact of Preventive Interventions

Overview of attention for article published in Scientific Reports, May 2013
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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 (80th percentile)
  • Good Attention Score compared to outputs of the same age and source (68th percentile)

Mentioned by

news
1 news outlet

Readers on

mendeley
22 Mendeley
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Article details
Title
Discrete Event Simulation Model of Sudden Cardiac Death Predicts High Impact of Preventive Interventions
Published in
Scientific Reports, May 2013
DOI 10.1038/srep01771
Pubmed ID
Authors
Abstract

Sudden Cardiac Death (SCD) is responsible for at least 180,000 deaths a year and incurs an average cost of $286 billion annually in the United States alone. Herein, we present a novel discrete event simulation model of SCD, which quantifies the chains of events associated with the formation, growth, and rupture of atheroma plaques, and the subsequent formation of clots, thrombosis and on-set of arrhythmias within a population. The predictions generated by the model are in good agreement both with results obtained from pathological examinations on the frequencies of three major types of atheroma, and with epidemiological data on the prevalence and risk of SCD. These model predictions allow for identification of interventions and importantly for the optimal time of intervention leading to high potential impact on SCD risk reduction (up to 8-fold reduction in the number of SCDs in the population) as well as the increase in life expectancy.

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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 22 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Master 6 27%
Other 5 23%
Researcher 4 18%
Student > Ph. D. Student 2 9%
Professor 1 5%
Other 1 5%
Unknown 3 14%
Readers by discipline
Readers by discipline Count As %
Computer Science 5 23%
Medicine and Dentistry 4 18%
Engineering 3 14%
Nursing and Health Professions 2 9%
Agricultural and Biological Sciences 2 9%
Other 2 9%
Unknown 4 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 07 May 2013.
All research outputs
#4,155,390
of 22,712,476 outputs
Outputs from Scientific Reports
#32,693
of 122,405 outputs
Outputs of similar age
#35,739
of 193,543 outputs
Outputs of similar age from Scientific Reports
#147
of 475 outputs
Altmetric has tracked 22,712,476 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 122,405 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.2. This one has gotten more attention than average, scoring higher than 72% 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 193,543 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 80% of its contemporaries.
We're also able to compare this research output to 475 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 68% of its contemporaries.