The Extent of Subclinical Atherosclerosis Is Partially Predicted by the Inflammatory Load: A Prospective Study over 5 Years in Patients with Rheumatoid Arthritis and Matched Controls
Bibliographic record
Abstract
OBJECTIVE: This prospective followup study investigated subclinical atherosclerosis in relation to traditional cardiovascular disease (CVD) risk factors and inflammation in patients with rheumatoid arthritis (RA) recruited at diagnosis compared with controls. METHODS: Patients diagnosed with early RA were consecutively recruited into a prospective study. From these, a subgroup aged ≤ 60 years (n = 71) was consecutively included for ultrasound measurement of intima-media thickness (IMT) and flow-mediated dilation (FMD) at inclusion (T0) and after 5 years (T5). Age- and sex-matched controls (n = 40) were also included. RESULTS: In the Wilcoxon signed-rank test, both IMT and FMD were significantly aggravated at T5 compared to baseline in patients with RA, whereas only IMT was significantly increased in controls. In univariate linear regression analyses among patients with RA, the IMT at T5 was significantly associated with age, systolic blood pressure (BP), cholesterol, triglycerides, Systematic Coronary Risk Evaluation (SCORE), and Reynolds Risk Score at baseline (p < 0.05). Similarly, FMD at T5 was significantly inversely associated with age, smoking, systolic BP, SCORE, and Reynolds Risk Score (p < 0.05). A model with standardized predictive value from multiple linear regression models including age, smoking, BP, and blood lipids at baseline significantly predicted the observed value of IMT after 5 years. When also including the area under the curve for the 28-joint Disease Activity Score over 5 years, the observed value of IMT was predicted to a large extent. CONCLUSION: This prospective study identified an increased subclinical atherosclerosis in patients with RA. In the patients with RA, several traditional CVD risk factors at baseline significantly predicted the extent of subclinical atherosclerosis 5 years later. The inflammatory load over time augmented this prediction.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".