| Title |
Genetic Risk Prediction for Primary and Secondary Prevention of Atherosclerotic Cardiovascular Disease: an Update
|
|---|---|
| Published in |
Current Cardiology Reports, March 2018
|
| DOI | 10.1007/s11886-018-0980-0 |
| Pubmed ID | |
| Authors |
Christopher Labos, George Thanassoulis |
| Abstract |
This review aims to summarize the research on genetic risk scores and their ability to improve risk prediction in both a primary and a secondary prevention population. Several groups have examined the role of genetic scores in different patient populations. Recent studies have capitalized on the growing number of identified genetic variants to construct polygenic risk scores that include hundreds and sometimes thousands of SNPs. Also, recent studies have demonstrated that individuals with high genetic risk scores can attenuate their risk with lifestyle modifications and with statins, for which the benefit of treatment may be greater in those at highest genetic risk. Genetic risk scores when added to existing clinical models appear to improve risk prediction, particularly in the setting of incident cardiovascular disease and may provide actionable information to optimize prevention early in life. Future research will need to establish how to best use this genetic risk information either as a means to further individualize treatment decisions or to better identify high-risk populations. |
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 % |
|---|---|---|
| Canada | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 24 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 21% |
| Student > Master | 4 | 17% |
| Professor | 2 | 8% |
| Student > Ph. D. Student | 2 | 8% |
| Student > Bachelor | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 9 | 38% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 5 | 21% |
| Biochemistry, Genetics and Molecular Biology | 1 | 4% |
| Agricultural and Biological Sciences | 1 | 4% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 4% |
| Decision Sciences | 1 | 4% |
| Other | 3 | 13% |
| Unknown | 12 | 50% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 05 April 2018.
All research outputs
#14,381,804
of 23,031,582 outputs
Outputs from Current Cardiology Reports
#559
of 1,003 outputs
Outputs of similar age
#188,117
of 331,324 outputs
Outputs of similar age from Current Cardiology Reports
#10
of 25 outputs
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We're also able to compare this research output to 25 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 60% of its contemporaries.