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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Challenges of developing a cardiovascular risk calculator for patients with rheumatoid arthritis
|
|---|---|
| Published in |
PLOS ONE, March 2017
|
| DOI | 10.1371/journal.pone.0174656 |
| Pubmed ID | |
| Authors |
Cynthia S. Crowson, Silvia Rollefstad, George D. Kitas, Piet L. C. M. van Riel, Sherine E. Gabriel, Anne Grete Semb, On behalf of A Trans-Atlantic Cardiovascular Risk Consortium for Rheumatoid Arthritis |
| Abstract |
Cardiovascular disease (CVD) risk calculators designed for use in the general population do not accurately predict the risk of CVD among patients with rheumatoid arthritis (RA), who are at increased risk of CVD. The process of developing risk prediction models involves numerous issues. Our goal was to develop a CVD risk calculator for patients with RA. Thirteen cohorts of patients with RA originating from 10 different countries (UK, Norway, Netherlands, USA, Sweden, Greece, South Africa, Spain, Canada and Mexico) were combined. CVD risk factors and RA characteristics at baseline, in addition to information on CVD outcomes were collected. Cox models were used to develop a CVD risk calculator, considering traditional CVD risk factors and RA characteristics. Model performance was assessed using measures of discrimination and calibration with 10-fold cross-validation. A total of 5638 RA patients without prior CVD were included (mean age: 55 [SD: 14] years, 76% female). During a mean follow-up of 5.8 years (30139 person years), 389 patients developed a CVD event. Event rates varied between cohorts, necessitating inclusion of high and low risk strata in the models. The multivariable analyses revealed 2 risk prediction models including either a disease activity score including a 28 joint count and erythrocyte sedimentation rate (DAS28ESR) or a health assessment questionnaire (HAQ) along with age, sex, presence of hypertension, current smoking and ratio of total cholesterol to high-density lipoprotein cholesterol. Unfortunately, performance of these models was similar to general population CVD risk calculators. Efforts to develop a specific CVD risk calculator for patients with RA yielded 2 potential models including RA disease characteristics, but neither demonstrated improved performance compared to risk calculators designed for use in the general population. Challenges encountered and lessons learned are discussed in detail. |
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 % |
|---|---|---|
| United States | 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 89 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 1 | 1% |
| Unknown | 88 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 12 | 13% |
| Other | 9 | 10% |
| Student > Postgraduate | 9 | 10% |
| Student > Master | 8 | 9% |
| Student > Bachelor | 7 | 8% |
| Other | 19 | 21% |
| Unknown | 25 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 37 | 42% |
| Nursing and Health Professions | 4 | 4% |
| Computer Science | 3 | 3% |
| Pharmacology, Toxicology and Pharmaceutical Science | 3 | 3% |
| Engineering | 3 | 3% |
| Other | 11 | 12% |
| Unknown | 28 | 31% |
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 27 March 2017.
All research outputs
#20,233,045
of 25,728,855 outputs
Outputs from PLOS ONE
#176,849
of 224,062 outputs
Outputs of similar age
#236,022
of 323,585 outputs
Outputs of similar age from PLOS ONE
#3,268
of 4,597 outputs
Altmetric has tracked 25,728,855 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 224,062 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.8. This one is in the 17th percentile – i.e., 17% 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 323,585 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 4,597 others from the same source and published within six weeks on either side of this one. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.