Coronary and Abdominal Aorta Calcification in Rheumatoid Arthritis: Relationships with Traditional Cardiovascular Risk Factors, Disease Characteristics, and Concomitant Treatments
Bibliographic record
Abstract
OBJECTIVE: To assess the influence of traditional cardiovascular (CV) risk factors, disease characteristics, and concomitant treatments in patients with rheumatoid arthritis (RA) on coronary artery calcification (CAC) and abdominal aorta calcification (AAC). METHODS: In our cross-sectional study, 75 patients with RA were compared with 75 age-matched and sex-matched control participants. The CAC and AAC scores were measured by computed tomography in patients with no clinical evidence of coronary artery disease. The relationships between the presence or absence of CAC and AAC and traditional CV risk factors, disease characteristics, and concomitant treatments in patients with RA were assessed in a multiple logistic regression analysis. RESULTS: The RA and control groups did not differ significantly in terms of age, sex composition, or the prevalence of traditional CV risk factors. AAC and CAC were more prevalent and severe in patients with RA than in controls. Older age (OR=1.15, p<0.01) and hypertension (OR=3.77, p=0.04) were found to be independently associated with CAC, whereas current use of methotrexate (MTX; OR=0.12, p=0.01) was found to be associated with the absence of CAC. Older age (OR per yr=1.17, p<0.001) and erosive arthritis (OR=3.78, p=0.03) were found to be independently associated with AAC. CONCLUSION: Our study demonstrates that in patients with RA, (1) CAC and AAC are more prevalent and more severe compared with age-matched and sex-matched control participants, (2) current use of MTX is a major determinant of the absence of CAC, and (3) erosive arthritis is a major determinant of AAC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".