Carotid Artery Atherosclerosis in Patients with Active Rheumatoid Arthritis: Predictors of Plaque Occurrence and Progression Over 24 Weeks
Bibliographic record
Abstract
INTRODUCTION: This study evaluated the prevalence and progression of subclinical carotid artery atherosclerosis in active rheumatoid arthritis (RA). METHODS: Carotid arteries of RA patients were scanned using 3D ultrasound at baseline and 24 weeks for total plaque area, vessel wall volume, and intima-media thickness (IMT), as well as arterial stiffness measured using pulse wave velocity. Variables related to inflammation, lipids and cardiovascular (CV) risk were assessed for associations with plaque progression. Of 195 screened patients, 31 met inclusion criteria (66 Swollen joint count (SJC) plus 68 Tender joint count (TJC)≥8 OR SJC plus TJC≥4 with elevated acute phase reactants) and were enrolled (27 female; mean age 59.3±9.8years). Patients using lipid lowering drugs and uncontrolled comorbidities were excluded. RESULTS: Atherosclerotic plaque occurred in 35% and arterial wall hypertrophy (IMT≥0.6mm) in 86% of patients. Most (68%) had an abnormal lipid profile characterized by reduced HDL and/or increased total cholesterol/HDL index, which was adversely affected by disease activity. Stepwise binary logistic regression analysis showed that Framingham risk score (OR=1.155, 95%CI:1.002-1.332, p=0.046) and ESR (OR=1.148, 95%CI:1.015-1.299, p=0.028) predicted plaque burden most strongly. Plaque progression was significantly associated with baseline higher hsCRP, ESR, and heavy smoking, but only hsCRP predicted plaque growth in multivariate regression analysis (p=0.004); and hsCRP was related to higher disease activity (r=0.443, p=0.016), LDL (r=0.544, p=0.007), and smoking (r=0.384, p=0.04). CONCLUSION: RA-related inflammation contributed to augmented CV burden in RA and might mediate its effect on atherosclerosis through hsCRP and modulation of the traditional CV risk factors, such as dyslipidemia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".