Modest increases in serum calcidiol may improve T2DM‐related health outcomes in non‐white, ethnically diverse, postmenopausal women (LB327)
Bibliographic record
Abstract
Mounting evidence suggests a crucial role for vitamin D status in the pathogenesis of type 2 diabetes mellitus (T2DM), since vitamin D promotes the survival and function of pancreatic β‐cells. Our objectives were to examine the correlation between serum calcidiol and diabetes‐related health outcomes, and to determine whether vitamin D3 and calcium supplementation would attenuate the severity of T2DM. In this pilot study, 11 non‐white, ethnically diverse (Caribbean, Black, South Asian), post‐menopausal women with T2DM (age, 61 ± 11 y) were supplemented for 3 y with either placebo or 1800 IU of vitamin D3 + 720 mg of calcium (CaD)/day. Spearman’s rank coefficient was used to examine the correlations between serum calcidiol and the different outcome measures. Per‐protocol and retrospective analyses were adopted to determine the effect of CaD on the outcome measures. Significance was established at P 蠄 0.10. The relative change over 3 y in serum calcidiol significantly correlated with the relative change in body weight (r = ‐0.736, P = 0.005), BMI (r = ‐0.736, P = 0.005), body fat (%) (r = ‐0.445, P = 0.085), hip circumference (r = ‐0.664, P = 0.013), serum TC/HDL‐C (r = ‐0.427, P = 0.095), serum PTH (r = ‐0.655, P = 0.014), and serum calcium (r = 0.500, P = 0.059). Retrospective analysis showed differences between the CaD vs. placebo in serum calcidiol (+41.7% vs. ‐30.3%, respectively, P = 0.004), hip circumference (‐3.25% vs. +0.32%, respectively, P = 0.052), systolic blood pressure (‐1.5% vs. +12.0%, respectively, P = 0.126), and serum PTH (‐30.8% vs. ‐3.1 %, respectively, P = 0.003). We conclude that modest increases in serum calcidiol may improve T2DM‐related health outcomes in non‐white, ethnically diverse, postmenopausal women.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".