Decreased Cardiovascular Mortality in Patients with Incident Rheumatoid Arthritis (RA) in Recent Years: Dawn of a New Era in Cardiovascular Disease in RA?
Bibliographic record
Abstract
OBJECTIVE: To assess trends in cardiovascular (CV) mortality in patients with incident rheumatoid arthritis (RA) in 2000-07 versus the previous decades, compared with non-RA subjects. METHODS: The study population consisted of Olmsted County, Minnesota, USA residents with incident RA (age ≥ 18 yrs, 1987 American College of Rheumatology criteria was met in 1980-2007) and non-RA subjects from the same underlying population with similar age, sex, and calendar year of index. All subjects were followed until death, migration, or December 31, 2014. Followup was truncated for comparability. Aalen-Johansen methods were used to estimate CV mortality rates, adjusting for competing risk of other causes. Cox proportional hazards models were used to compare CV mortality by decade. RESULTS: The study included 813 patients with RA and 813 non-RA subjects (mean age 55.9 yrs; 68% women for both groups). Patients with incident RA in 2000-07 had markedly lower 10-year overall CV mortality (2.7%, 95% CI 0.6-4.9%) and coronary heart disease (CHD) mortality (1.1%, 95% CI 0.0-2.7%) than patients diagnosed in 1990-99 (7.1%, 95% CI 3.9-10.1% and 4.5%, 95% CI 1.9-7.1%, respectively; HR for overall CV death: 0.43, 95% CI 0.19-0.94; CHD death: HR 0.21, 95% CI 0.05-0.95). This improvement in CV mortality persisted after accounting for CV risk factors. Ten-year overall CV mortality and CHD mortality in 2000-07 RA incidence cohort was similar to non-RA subjects (p = 0.95 and p = 0.79, respectively). CONCLUSION: Our findings suggest significantly improved overall CV mortality, particularly CHD mortality, in patients with RA in recent years. Further studies are needed to examine the reasons for this improvement.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".