Abstract 12100: Association Between Rheumatoid Arthritis and Cardiovascular Outcomes: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Rheumatoid arthritis (RA) is an autoimmune disorder with a varying range of organs involved and leading to adverse outcomes. However, very little is known, with conflicting results about the association between RA and atrial fibrillation (AF) and the incidence of acute coronary syndrome (ACS). Objective: We aim to evaluate the incidence of atrial fibrillation (AF), ACS, and other clinical outcomes among RA patients. Methods: We performed a systematic literature search using PubMed, Embase, and Scopus for relevant articles from inception until 10th April 2023. Primary clinical outcomes were AF. Secondary endpoints were acute coronary syndrome (ACS), stroke, and all-cause of mortality. Results: A total of 4,667,199 patients were included in the analysis, with 77460 (xy%) patients in the RA group and 4589739 patients in the NRA group. The most common Comorbidity includes hypertension among RA and NRA groups (27% vs. 6%), respectively. Pooled analysis of primary outcomes shows that RA groups of patients had significantly higher odds AF (OR, 1.17(95%CI: 1.11-1.23), P<0.00001, I2=34%) compared with NRA groups. Secondary Outcomes shows that the RA group of patients had significantly higher odds of ACS (OR, 1.37(95%CI: 1.23-1.53), P<0.00001) compared with the NRA groups. However, the likelihood of stroke (OR, 1.02(95%CI: 0.95-1.08), P=0.65), and all cause mortality (OR, 1.25(95%CI: 0.84-1.87), P=0.27, I2=91%) was comparable between both the groups of patients. Conclusion: Our study shows that RA groups of patients are at increased risk of having atrial fibrillation and acute coronary syndrome. However, mortality risk was comparable between both groups.
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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 | 0.009 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.029 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".