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American College of Cardiology

Improving the Use of Primary Prevention Implantable Cardioverter-Defibrillators Therapy With Validated Patient-Centric Risk Estimates

Overview of attention for article published in JACC: Clinical Electrophysiology, June 2018
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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 (90th percentile)
  • Good Attention Score compared to outputs of the same age and source (72nd percentile)

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2 news outlets
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13 X users

Citations

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16 Dimensions

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28 Mendeley
Title
Improving the Use of Primary Prevention Implantable Cardioverter-Defibrillators Therapy With Validated Patient-Centric Risk Estimates
Published in
JACC: Clinical Electrophysiology, June 2018
DOI 10.1016/j.jacep.2018.04.015
Pubmed ID
Authors

Wayne C. Levy, Anne S. Hellkamp, Daniel B. Mark, Jeanne E. Poole, Ramin Shadman, Todd F. Dardas, Jill Anderson, George Johnson, Daniel P. Fishbein, Kerry L. Lee, David T. Linker, Gust H. Bardy

Abstract

The authors previously developed the Seattle Proportional Risk Model (SPRM) in systolic heart failure patients without implantable cardioverter-defibrillators (ICDs)to predict the proportion of deaths that were sudden. They subsequently validated the SPRM in 2 observational ICD data sets. The objectives in the present study were to determine whether this validated model could improve identification of clinically important variations in the expected magnitude of ICD survival benefit by using a pivotal randomized trial of primary prevention ICD therapy. Recent data show that <50% of nominally eligible subjects receive guideline- recommended primary prevention ICDs. In the SCD-HeFT (Sudden Cardiac Death in Heart Failure Trial), a placebo-controlled ICD trial in 2,521 patients with an ejection fraction ≤35% and symptomatic heart failure, we tested the use of patient-level SPRM-predicted probability of sudden death (relative to that of non-sudden death) as a summary measurement of the potential for ICD benefit. A Cox proportional hazards model was used to estimate variations in the relationship between patient-level SPRM predictions and ICD benefit. Relative to use of mortality predictions with the Seattle Heart Failure Model, the SPRM was much better at partitioning treatment benefit from ICD therapy (effect size was 2- to 3.6-fold larger for the ICD×SPRM interaction). ICD benefit varied significantly across SPRM-predicted risk quartiles: for all-cause mortality, a +10% increase with ICD therapy in the first quartile (highest risk of death, lowest proportion of sudden death) to a decrease of 66% in the fourth quartile (lowest risk of death, highest proportion of sudden death; p = 0.0013); for sudden death mortality, a 19% reduction in SPRM quartile 1 to 95% reduction in SPRM quartile 4 (p < 0.0001). In symptomatic systolic heart failure patients with a Class I recommendation for primary prevention ICD therapy, the SPRM offers a useful patient-centric tool for guiding shared decision making.

X Demographics

X Demographics

The data shown below were collected from the profiles of 13 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 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 18%
Other 4 14%
Professor > Associate Professor 3 11%
Student > Master 3 11%
Student > Bachelor 1 4%
Other 4 14%
Unknown 8 29%
Readers by discipline Count As %
Medicine and Dentistry 16 57%
Social Sciences 2 7%
Biochemistry, Genetics and Molecular Biology 1 4%
Unknown 9 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 24. 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 15 September 2018.
All research outputs
#1,550,940
of 25,385,509 outputs
Outputs from JACC: Clinical Electrophysiology
#348
of 1,554 outputs
Outputs of similar age
#32,485
of 342,755 outputs
Outputs of similar age from JACC: Clinical Electrophysiology
#11
of 40 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,554 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.9. This one has done well, scoring higher than 77% 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 342,755 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 40 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 72% of its contemporaries.