Anticyclic Citrullinated Peptide Antibodies and Rheumatoid Factor as Risk Factors for 10-year Cardiovascular Morbidity in Patients with Rheumatoid Arthritis: A Large Inception Cohort Study
Bibliographic record
Abstract
Objective. To determine whether anticyclic citrullinated peptide antibodies (anti-CCP) and rheumatoid factor (RF) are risk factors for 10-year cardiovascular disease (CVD) in patients with rheumatoid arthritis (RA). Methods. Analyses were performed using data from the Nijmegen early RA inception cohort, in which patients with newly diagnosed RA, consecutively included since 1985, were regularly followed up. Anti-CCP and RF were determined at baseline (diagnosis). Outcome was the first cardiovascular disease (CVD) event [ischemic heart disease, nonhemorrhagic cerebrovascular accident (CVA), or peripheral artery disease (PAD)] after baseline as retrieved from physician diagnosis. Fatality was checked against death certificates. Cox regression including correction for baseline confounders was performed to estimate the effect of anti-CCP, RF, and their interaction on 10-year CVD-free survival. Results. Of 929 patients included, 628 were anti-CCP–positive and 697 were RF-positive. During followup, with a median of 7.5 years, 162 CV events were observed (101 ischemic heart disease, 45 CVA, and 16 PAD), of which 15 were fatal. The HRadjusted for anti-CCP was 1.17 (95% CI 0.82–1.67) and the HRadjusted for RF was 1.52 (95% CI 1.00–2.30). The association of RF positivity with CVD was even stronger in the anti-CCP–negative patients: HRadjusted 2.09 (95% CI 1.18–3.71). There was no significant interaction (p = 0.098) between anti-CCP and RF. Conclusion. Rather than anti-CCP, presence of RF was associated with CVD in this cohort of patients with RA.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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".