Risk of cardiovascular mortality in patients with rheumatoid arthritis: A meta‐analysis of observational studies
Bibliographic record
Abstract
OBJECTIVE: To determine the magnitude of risk of cardiovascular mortality in patients with rheumatoid arthritis (RA) compared with the general population through a meta-analysis of observational studies. METHODS: We searched Medline, EMBase, and Lilacs databases from their inception to July 2005. Observational studies that met the following criteria were assessed by 2 researchers: 1) prespecified RA definition, 2) clearly defined cardiovascular disease (CVD) outcome, including ischemic heart disease (IHD) and cerebrovascular accidents (CVAs), and 3) reported standardized mortality ratios (SMRs) and 95% confidence intervals (95% CIs). We calculated weighted-pooled summary estimates of SMRs (meta-SMRs) for CVD, IHD, and CVAs using the random-effects model, and tested for heterogeneity using the I(2) statistic. RESULTS: Twenty-four studies met the inclusion criteria, comprising 111,758 patients with 22,927 cardiovascular events. Overall, there was a 50% increased risk of CVD death in patients with RA (meta-SMR 1.50, 95% CI 1.39-1.61). Mortality risks for IHD and CVA were increased by 59% and 52%, respectively (meta-SMR 1.59, 95% CI 1.46-1.73 and meta-SMR 1.52, 95% CI 1.40-1.67, respectively). We identified asymmetry in the funnel plot (Egger's test P = 0.002), as well as significant heterogeneity in all main analyses (P < 0.0001). Subgroup analyses showed that inception cohort studies (n = 4, comprising 2,175 RA cases) were the only group that did not show a significantly increased risk for CVD (meta-SMR 1.19, 95% CI 0.86-1.68). CONCLUSION: Published data indicate that CVD mortality is increased by approximately 50% in RA patients compared with the general population. However, we found that study characteristics may influence the estimate.
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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 | 0.031 | 0.049 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.057 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".