Cardiovascular Event Risk in Rheumatoid Arthritis Compared with Type 2 Diabetes: A 15-year Longitudinal Study
Bibliographic record
Abstract
OBJECTIVE: Cardiovascular (CV) disease (CVD) risk is increased in rheumatoid arthritis (RA). However, longterm followup studies investigating this risk are scarce. METHODS: The CARRÉ (CARdiovascular research and RhEumatoid arthritis) study is a prospective cohort study investigating CVD and its risk factors in 353 patients with longstanding RA. CV endpoints were assessed at baseline and 3, 10, and 15 years after the start of the study and are compared to a reference cohort (n = 2540), including a large number of patients with type 2 diabetes (DM). RESULTS: Ninety-five patients with RA developed a CV event over 2973 person-years, resulting in an incidence rate of 3.20 per 100 person-years. Two hundred fifty-seven CV events were reported in the reference cohort during 18,874 person-years, resulting in an incidence rate of 1.36 per 100 person-years. Age- and sex-adjusted HR for CV events were increased for RA (HR 2.07, 95% CI 1.57-2.72, p < 0.01) and DM (HR 1.51, 95% CI 1.02-2.22, p = 0.04) compared to the nondiabetic participants. HR was still increased in RA (HR 1.82, 95% CI 1.32-2.50, p < 0.01) after additional adjustment for CV risk factors. Patients with both RA and DM or insulin resistance had the highest HR for developing CVD (2.21, 95% CI 1.01-4.80, p = 0.046 and 2.67, 95% CI 1.30-5.46, p < 0.01, respectively). CONCLUSION: The incidence rate of CV events in established RA was more than double that of the general population. Patients with RA have an even higher risk of CVD than patients with DM. This risk remained after adjustment for traditional CV risk factors, suggesting that systemic inflammation is an independent contributor to CV risk.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".