↓ Skip to main content

Scar heterogeneity on cardiovascular magnetic resonance as a predictor of appropriate implantable cardioverter defibrillator therapy

Overview of attention for article published in Critical Reviews in Diagnostic Imaging, April 2013
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
26 Dimensions

Readers on

mendeley
57 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Scar heterogeneity on cardiovascular magnetic resonance as a predictor of appropriate implantable cardioverter defibrillator therapy
Published in
Critical Reviews in Diagnostic Imaging, April 2013
DOI 10.1186/1532-429x-15-31
Pubmed ID
Authors

Hussein Rayatzadeh, Alex Tan, Raymond H Chan, Shalin J Patel, Thomas H Hauser, Long Ngo, Jaime L Shaw, Susie N Hong, Peter Zimetbaum, Alfred E Buxton, Mark E Josephson, Warren J Manning, Reza Nezafat

Abstract

BACKGROUND: Despite the survival benefit of implantable-cardioverter-defibrillators (ICDs), the vast majority of patients receiving an ICD for primary prevention do not receive ICD therapy. We sought to assess the role of heterogeneous scar area (HSA) identified by late gadolinium enhancement cardiovascular magnetic resonance (LGE-CMR) in predicting appropriate ICD therapy for primary prevention of sudden cardiac death (SCD). METHODS: From September 2003 to March 2011, all patients who underwent primary prevention ICD implantation and had a pre-implantation LGE-CMR were identified. Scar size was determined using thresholds of 4 and 6 standard deviations (SD) above remote normal myocardium; HSA was defined using 3 different criteria; as the region between 2 SD and 4 SD (HSA2-4SD),between 2SD and 6SD (HSA2-6SD), and between 4SD and 6SD (HSA4-6SD). The end-point was appropriate ICD therapy. RESULTS: Out of 40 total patients followed for 25 +/- 24 months, 7 had appropriate ICD therapy. Scar size measured by different thresholds was similar in ICD therapy and non-ICD therapy groups (P = NS for all). However, HSA2-4SD and HSA4-6SD were significantly larger in the ICD therapy group (P = 0.001 and P = 0.03, respectively). In multivariable model HSA2-4SD was the only significant independent predictor of ICD therapy (HR = 1.08, 95%CI: 1.00-1.16, P = 0.04). Kaplan-Meier analysis showed that patients with greater HSA2-4SD had a lower survival free of appropriate ICD therapy (P = 0.026). CONCLUSIONS: In primary prevention ICD implantation, LGE-CMR HSA identifies patients with appropriate ICD therapy. If confirmed in larger series, HSA can be used for risk stratification in primary prevention of SCD.

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 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 2%
Unknown 56 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 19%
Student > Ph. D. Student 8 14%
Student > Postgraduate 5 9%
Student > Bachelor 5 9%
Professor 4 7%
Other 14 25%
Unknown 10 18%
Readers by discipline Count As %
Medicine and Dentistry 32 56%
Unspecified 3 5%
Computer Science 1 2%
Agricultural and Biological Sciences 1 2%
Chemistry 1 2%
Other 1 2%
Unknown 18 32%
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 12 April 2013.
All research outputs
#23,084,818
of 25,728,855 outputs
Outputs from Critical Reviews in Diagnostic Imaging
#1,293
of 1,386 outputs
Outputs of similar age
#187,428
of 213,378 outputs
Outputs of similar age from Critical Reviews in Diagnostic Imaging
#11
of 21 outputs
Altmetric has tracked 25,728,855 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,386 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one is in the 1st percentile – i.e., 1% 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 213,378 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 21 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.