Cardiovascular Disease Reduction in Rheumatoid Arthritis by Statins: The Final Evidence?
Bibliographic record
Abstract
The risk of cardiovascular disease (CVD) in patients with rheumatoid arthritis (RA) is considerably higher than in the general population and equals that in patients with diabetes1. The most convincing study in this respect comes from Denmark2. The study, which coupled nationwide registers to identify persons with new-onset RA, new-onset diabetes, and persons who had a first myocardial infarction (MI), comprised more than 4.3 million persons, of whom about 10,500 developed RA and 130,000 diabetes. The incidence rate ratio (IRR) of MI in RA was 1.7 (95% CI 1.5–1.9); identical to the risk in diabetes: IRR 1.7 (95% CI 1.6–1.8). Therefore, just as in diabetes, CVD risk management is also needed for RA. CVD risk management starts with assessment of the cardiovascular risk profile (with determination of blood pressure, smoking status, and lipid profile). On the basis of these data and risk calculators such as Framingham and the Systematic Coronary Risk Evaluation, the 10-year cardiovascular risk of a particular person can be calculated. Primary prevention involving treatment with statins and/or antihypertensive agents is then only indicated when this 10-year risk is above a certain value. However, there is little evidence about the outcome of this strategy, particularly for statin treatment. Despite the fact that the increased cardiovascular risk in RA is well known — and thus the need for CVD prevention — numerous recent reports indicate that CVD risk management is still poorly implemented. One of the reasons might be … Address correspondence to Prof. M.T. Nurmohamed, Amsterdam Rheumatology and Immunology Center | Reade – Rheumatology, Jan van Breemenstraat 2, Amsterdam 1056AB, the Netherlands; E-mail: m.nurmohamed{at}reade.nl
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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 | 0.012 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.006 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".