Predictive Value of Arterial Stiffness and Subclinical Carotid Atherosclerosis for Cardiovascular Disease in Patients with Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: We evaluated the predictive value of these vascular biomarkers for cardiovascular disease (CVD) events in patients with rheumatoid arthritis (RA): aortic pulse wave velocity (aPWV), augmentation index (AIx), carotid intima-media thickness (cIMT), and carotid plaques (CP). They are often used as risk markers for CVD. METHODS: In 2007, 138 patients with RA underwent clinical examination, laboratory tests, blood pressure testing, and vascular biomarker measurements. Occurrence of CVD events was recorded in 2013. Predictive values were assessed in Kaplan-Meier plots, log-rank, and crude and adjusted Cox proportional hazard (PH) regression analyses. RESULTS: Baseline median age and disease duration was 59.0 years and 17.0 years, respectively, and 76.1% were women. CVD events occurred in 10 patients (7.2%) during a mean followup of 5.4 years. Compared with patients with low aPWV, AIx, cIMT, and without CP, patients with high aPWV (p < 0.001), high AIx (p = 0.04), high cIMT (p = 0.01), and CP (p < 0.005) at baseline experienced more CVD events. In crude Cox PH regression analyses, aPWV (p < 0.001), cIMT (p < 0.001), age (p = 0.01), statin (p = 0.01), and corticosteroid use (p = 0.01) were predictive of CVD events, while AIx was nonsignificant (p = 0.19). The Cox PH regression estimates for vascular biomarkers were not significantly altered when adjusting individually for demographic variables, traditional CVD risk factors, RA disease-related variables, or medication. All patients who developed CVD had CP at baseline. CONCLUSION: CP, aPWV, and cIMT were predictive of CVD events in this cohort of patients with RA. Future studies are warranted to examine the additive value of arterial stiffness and carotid atherosclerosis markers in CVD risk algorithms. Regional Ethical Committee approval numbers 2009/1582 and 2009/1583.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".