Circulating Vitamin D Metabolites and Subclinical Atherosclerosis in Type 1 Diabetes
Bibliographic record
Abstract
OBJECTIVE: People with type 1 diabetes are at high risk of premature atherosclerosis. Existing evidence suggests that impaired vitamin D metabolism may contribute to the development of atherosclerosis. We tested associations of circulating vitamin D metabolite concentrations with subclinical atherosclerosis among 1,193 participants with type 1 diabetes in the DCCT/EDIC study. RESEARCH DESIGN AND METHODS: We measured plasma concentrations of 25-hydroxyvitamin D [25(OH)D], 1,25-dihydroxyvitamin D, and 24,25-dihydroxyvitamin D by mass spectrometry at the end of the DCCT. In a staggered cross-sectional design, we tested associations with coronary artery calcium (CAC), measured by computed tomography a median of 10 years later, and with common and internal carotid intima-media thickness (IMT), measured by B-mode ultrasonography on two occasions a median of 4 years later and a median of 10 years later. We hypothesized that lower concentrations of each vitamin D metabolite would be associated with increased risk of CAC and greater carotid IMT. RESULTS At the time metabolites were measured, mean age was 32.4 years and mean duration of diabetes was 7.5 years. The prevalence and severity of CAC tended to be lower-not higher-with lower concentrations of each vitamin D metabolite. For instance, in a fully adjusted multinomial logistic model, a 25 nmol/L lower 25-hydroxyvitamin D was associated with a 0.8-fold decrease in the odds of having higher CAC (95% CI 0.68-0.96, P = 0.01). No vitamin D metabolite was associated with either common or internal mean IMT. CONCLUSIONS: We did not find evidence linking impaired vitamin D metabolism with increased subclinical atherosclerosis in type 1 diabetes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".