Serum Uric Acid Is Associated with Carotid Plaques: The National Heart, Lung, and Blood Institute Family Heart Study
Bibliographic record
Abstract
OBJECTIVE: To examine the association of serum uric acid (SUA) with a marker of preclinical cardiovascular disease (CVD), carotid atherosclerotic plaques (PLQ), where early evidence of risk may be evident, focusing on individuals without CV risk factors. METHODS: The National Heart, Lung, and Blood Institute Family Heart Study is a multicenter study designed to assess risk factors for heart disease. PLQ were assessed with carotid ultrasound. We conducted sex-specific logistic regression to assess the association of SUA with presence of PLQ, including analyses among persons without risk factors related to both CVD and hyperuricemia. RESULTS: In total, 4,866 participants had both SUA and carotid ultrasound assessed (54% women, mean age 52 yrs, mean body mass index 27.6). The association of SUA with PLQ increased with increasing SUA levels, demonstrating a dose-response relation for men [OR 1.0, 1.29, 1.61, 1.75, for SUA categories < 5 (reference), 5 to < 6, 6 to < 6.8, >or= 6.8 mg/dl, respectively; p = 0.002]. Similar associations were found in men without CV risk factors. We found no relation of SUA with PLQ in women. CONCLUSION: In this large study, SUA was associated with carotid atherosclerotic plaques in men. Results were similar in the absence of CV risk factors. These results suggest that SUA may have a pathophysiologic role in atherosclerosis in men.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".