Correlations between plasma homocysteine and folate concentrations and carotid atherosclerosis in high-risk individuals: baseline data from the Homocysteine and Atherosclerosis Reduction Trial (HART)
Bibliographic record
Abstract
Homocysteine has been proposed as a risk factor for atherosclerosis. The association between plasma total homocysteine (tHcy) concentration and carotid atherosclerosis has not been thoroughly studied in high-risk populations with vascular disease. For this study, carotid atherosclerosis was assessed by measurements of carotid intima-media thickness (IMT) and plaque calcification in 923 patients with vascular disease or diabetes. Associations with tHcy and plasma folate concentrations were examined. The mean and single maximum carotid IMT were 1.27 +/- 0.34 mm and 2.41 +/- 0.83 mm, respectively. The mean segment plaque calcification score was 27.8%. tHcy correlated with mean (r = 0.13; p < 0.001) and single maximum (r = 0.12; p < 0.001) carotid IMT. There was a progressive increase in mean and single maximum carotid IMT across quartiles of tHcy (p < 0.0001 for trend). These associations were no longer significant after adjusting for other CV risk factors. A trend towards an inverse association between plasma folate and mean max carotid IMT was found in both univariate and multivariable analyses. However, the plaque calcification score increased across quartiles of tHcy (p < 0.01) and decreased across quartiles of plasma folate concentrations (p < 0.05) after multiple adjustments. In conclusion, in high-risk individuals, tHcy and low folate concentrations were only weakly associated with carotid IMT. In contrast, we found an independent association with the plaque calcification score, a measure of more advanced atherosclerosis. The effect of tHcy lowering on carotid atherosclerosis and stroke prevention warrants further investigation.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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".