The Influence of Rheumatoid Arthritis Disease Characteristics on Heart Failure
Bibliographic record
Abstract
OBJECTIVE: To examine the influence of rheumatoid arthritis (RA) characteristics and antirheumatic medications on the risk of heart failure (HF) in patients with RA. METHODS: A population-based incidence cohort of RA patients aged ≥ 18 years (1987 American College of Rheumatology criteria first met between January 1, 1980, and January 1, 2008) with no history of HF was followed until onset of HF (defined by Framingham criteria), death, or January 1, 2008. We collected data on RA characteristics, antirheumatic medications, and cardiovascular (CV) risk factors. Cox models adjusting for age, sex, and calendar year were used to analyze the data. RESULTS: The study included 795 RA patients [mean age 55.3 yrs, 69% women, 66% rheumatoid factor (RF)-positive]. During the mean followup of 9.7 years, 92 patients developed HF. The risk of HF was associated with RF positivity (HR 1.6, 95% CI 1.0, 2.5), erythrocyte sedimentation rate (ESR) at RA incidence (HR 1.6, 95% CI 1.2, 2.0), repeatedly high ESR (HR 2.1, 95% CI 1.2, 3.5), severe extraarticular manifestations (HR 3.1, 95% CI 1.9, 5.1), and corticosteroid use (HR 2.0, 95% CI 1.3, 3.2), adjusting for CV risk factors and coronary heart disease (CHD). Methotrexate users were half as likely to have HF as nonusers (HR 0.5, 95% CI 0.3, 0.9). CONCLUSION: Several RA characteristics and the use of corticosteroids were associated with HF, with adjustment for CV risk factors and CHD. Methotrexate use appeared to be protective against HF. These findings suggest an independent effect of RA on HF that may be further modified by antirheumatic treatment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".