| Title |
Adding multiple risk factors improves Framingham coronary heart disease risk scores
|
|---|---|
| Published in |
Vascular Health and Risk Management, September 2014
|
| DOI | 10.2147/vhrm.s69672 |
| Pubmed ID | |
| Authors |
Guizhou Hu, Martin Root, Ashlee W Duncan |
| Abstract |
Since the introduction of the Framingham Risk Score (FRS), numerous versions of coronary heart disease (CHD) prediction models have claimed improvement over the FRS. Tzoulaki et al challenged the validity of these claims by illustrating methodology deficiencies among the studies. However, the question remains: Is it possible to create a new CHD model that is better than FRS while overcoming the noted deficiencies? To address this, a new CHD prediction model was developed by integrating additional risk factors, using a novel modeling process. |
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.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 2% |
| Unknown | 59 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 12 | 20% |
| Student > Ph. D. Student | 10 | 17% |
| Student > Bachelor | 6 | 10% |
| Student > Doctoral Student | 4 | 7% |
| Researcher | 4 | 7% |
| Other | 11 | 18% |
| Unknown | 13 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 17 | 28% |
| Nursing and Health Professions | 9 | 15% |
| Biochemistry, Genetics and Molecular Biology | 3 | 5% |
| Agricultural and Biological Sciences | 2 | 3% |
| Computer Science | 2 | 3% |
| Other | 9 | 15% |
| Unknown | 18 | 30% |
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 07 April 2015.
All research outputs
#22,756,649
of 25,371,288 outputs
Outputs from Vascular Health and Risk Management
#747
of 804 outputs
Outputs of similar age
#213,024
of 248,664 outputs
Outputs of similar age from Vascular Health and Risk Management
#8
of 8 outputs
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