Carotid Plaque Characteristics and Disease Activity in Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: Carotid plaques (CP) are predictive of acute coronary syndrome in patients with rheumatoid arthritis (RA), suggesting that atherosclerotic plaques in these patients are vulnerable. The objective of our study was to characterize vulnerability of CP in patients with RA compared to a control population, and between RA patients with different levels of disease activity. METHODS: Ultrasound examination of carotid arteries was performed in 152 patients with RA and 89 controls. CP echolucency was evaluated by the Gray-Scale Median (GSM) technique. Lower GSM values indicate higher vulnerability of plaques. CP characteristics were compared between RA patients with active disease and in remission, and between patients and controls. All analyses were performed with adjustment for confounding factors (sex, age, smoking, and blood pressure). Poisson regression analysis was used for count data, mixed modeling for GSM and area per plaque, and analysis of covariance for minimum GSM value per patient. RESULTS: Patients with RA more frequently had CP (median 2, range 0, 4) compared with controls (median 1, range 0, 3; p < 0.001), after adjustment for age and sex. Patients with active RA disease according to the Clinical Disease Activity Index (CDAI) had lower median GSM (p = 0.03), minimum GSM (p = 0.03), and a larger CP area (although the latter finding was not significant; p = 0.27), compared with patients with RA in remission. These findings were not confirmed for other disease measures (Simplified Disease Activity Index, Disease Activity Score-28, C-reactive protein, erythrocyte sedimentation rate). CONCLUSION: Patients with RA had more CP compared with controls and patients in CDAI remission, and controls had more stable CP than patients with active disease; these findings point to the importance of achieving remission in RA.
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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 | 0.003 |
| 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 | 0.000 |
| 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".