Autoantibodies and the Risk of Cardiovascular Events
Bibliographic record
Abstract
OBJECTIVE: Inflammation and autoimmunity are associated with increased cardiovascular (CV) risk in patients with rheumatoid arthritis. This association may also be present in those without rheumatic diseases. Our purpose was to determine whether rheumatoid factor (RF), antinuclear antibody (ANA), and cyclic citrullinated peptide antibody (CCP) positivity are associated with increased risk of CV events and overall mortality in those with and without rheumatic diseases. METHODS: We performed a population-based cohort study of all subjects who had a RF and/or ANA test performed between January 1, 1990, and January 1, 2000, and/or CCP test performed between September 1, 2003, and January 1, 2005, with followup until April 1, 2007. Outcomes were ascertained using diagnostic indices from complete medical records, including CV events [myocardial infarction (MI), heart failure (HF), and peripheral vascular disease (PVD)] and mortality. Cox models were used to analyze the data. RESULTS: There were 6783 subjects with RF, 7852 with ANA, and 299 with CCP testing. Of these, 10.4%, 23.9%, and 14.7% were positive for RF, ANA, and CCP, respectively. Adjusting for age, sex, calendar year, comorbidity, and rheumatic disease, RF and ANA positivity were significant predictors of CV events [hazard ratio (HR) 1.24 and 1.26] and death (HR 1.43 and 1.18). Adjusting for age, CCP positivity was associated with CV events, but this association was not statistically significant (HR 3.1; 95% CI 0.8, 12.3). CONCLUSION: RF and ANA positivity are significant predictors of CV events and mortality in both those with and those without rheumatic diseases. These results support the role of immune dysregulation in the etiology of CV disease.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".