Title |
Coronary Risk Assessment by Point-Based vs. Equation-Based Framingham Models: Significant Implications for Clinical Care
|
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Published in |
Journal of General Internal Medicine, September 2010
|
DOI | 10.1007/s11606-010-1454-2 |
Pubmed ID | |
Authors |
William J. Gordon, Jesse M. Polansky, W. John Boscardin, Kathy Z. Fung, Michael A. Steinman |
Abstract |
US cholesterol guidelines use original and simplified versions of the Framingham model to estimate future coronary risk and thereby classify patients into risk groups with different treatment strategies. We sought to compare risk estimates and risk group classification generated by the original, complex Framingham model and the simplified, point-based version. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 50% |
Unknown | 1 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 50% |
Practitioners (doctors, other healthcare professionals) | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 26 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 6 | 23% |
Other | 5 | 19% |
Student > Bachelor | 4 | 15% |
Student > Doctoral Student | 2 | 8% |
Student > Postgraduate | 2 | 8% |
Other | 3 | 12% |
Unknown | 4 | 15% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 11 | 42% |
Agricultural and Biological Sciences | 3 | 12% |
Biochemistry, Genetics and Molecular Biology | 2 | 8% |
Nursing and Health Professions | 1 | 4% |
Computer Science | 1 | 4% |
Other | 3 | 12% |
Unknown | 5 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 16. 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 21 June 2018.
All research outputs
#2,136,465
of 23,911,072 outputs
Outputs from Journal of General Internal Medicine
#1,631
of 7,806 outputs
Outputs of similar age
#7,821
of 97,956 outputs
Outputs of similar age from Journal of General Internal Medicine
#14
of 47 outputs
Altmetric has tracked 23,911,072 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,806 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 21.8. This one has done well, scoring higher than 79% 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 97,956 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 92% of its contemporaries.
We're also able to compare this research output to 47 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 70% of its contemporaries.