Effect of Traditional Cardiovascular Risk Factors on the Independent Relationship of Leptin with Atherosclerosis in Rheumatoid Arthritis
Bibliographic record
Abstract
To the Editor: Leptin is an adipokine that regulates appetite and energy expenditure1. Both high and low leptin production can further increase cardiovascular (CV) risk1. Leptin is also produced in inflamed joints and implicated in the pathophysiology of rheumatoid arthritis (RA)2. Whether leptin increases CV risk in RA is currently uncertain. Two studies reported a lack of association between leptin concentrations and carotid artery intima-media thickness (cIMT) in RA3,4. Leptin concentrations were also found to be unrelated to coronary artery classification scores in RA5. However, we recently reported an independent relationship between leptin concentrations and surrogate markers of early atherogenesis in young patients with RA2. Importantly, in the present context, carotid artery plaque is a more reliable indicator of atherosclerosis than cIMT6. In our present study, we examined the independent relationships of leptin concentrations with cIMT and plaque in 217 (112 black and 105 white) patients with RA. Because the production and effects of adipokines on CV risk depend on pathophysiological context1,2,7, we also determined whether the presence of conventional and nonconventional CV risk factors modified leptin concentrations and their associations with atherosclerosis. … Address correspondence to Prof. P.H. Dessein, P.O. Box 1012, Melville 2109, Johannesburg, South Africa. E-mail: dessein{at}telkomsa.net
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".