The Role of Traditional Cardiovascular Risk Factors Among Patients with Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: People with rheumatoid arthritis (RA) have an increased risk of cardiovascular disease (CVD) compared with the general population. We investigated the relative contribution of traditional cardiovascular risk factors to this elevated risk. METHODS: Fifty RA subjects and 150 age and sex matched controls attended a cardiovascular risk assessment clinic betweenMarch and July 2006. Traditional cardiovascular risk factors and the absolute risks of CVD (calculated from application of a Framingham risk equation) were compared between the 2 groups. RESULTS: Compared with the controls, RA subjects were more likely to smoke (p<0.001), be physically inactive (p=0.006), and have higher mean measurements of body mass index (p=0.040) and waist circumference (p=0.049). No significant differences were found in mean levels of plasma lipid or glucose, or in the prevalences of diabetes and hypertension. Overall, the mean absolute risk of CVD was higher in the RA group, even after excluding smokers (p=0.036). CONCLUSION: Smoking and physical inactivity are important risk factors in the management of cardiovascular risk among patients with RA. Subjects with RA seem to have higher absolute risks of CVD compared with controls, even independently of smoking. This highlights the importance of treating all modifiable risk factors in those with RA although, individually, few may be conspicuous.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".