Pilot Study of Resveratrol in Older Adults With Impaired Glucose Tolerance
Bibliographic record
Abstract
BACKGROUND: Resveratrol, a plant-derived polyphenol, has shown promising effects on insulin sensitivity and glucose tolerance in animal models and is also reported to have cardioprotective properties, but human studies are limited. In a pilot study, we tested the hypothesis that resveratrol improves glucose metabolism and vascular function in older adults with impaired glucose tolerance (IGT). METHODS: Ten subjects aged 72 ± 3 years (M ± SD) with IGT were enrolled in a 4-week open-label study of resveratrol (daily dose 1, 1.5, or 2 g). Following a standard mixed meal (110 g carbohydrate, 20 g protein, 20 g fat), we measured 3-hour glucose and insulin area under the curve (AUC), insulin sensitivity (Matsuda index), and secretion (corrected insulin response at 30 minutes). Endothelial function was assessed by reactive hyperemia peripheral arterial tonometry (reactive hyperemia index) before and 90 minutes postmeal. Results did not differ by dose, so data were combined for analysis. RESULTS: At baseline, body mass index was 29 ± 5 kg/m(2), fasting plasma glucose 110 ± 13 mg/dL, and 2-hour glucose 183 ± 33 mg/dL. After 4 weeks of resveratrol, fasting plasma glucose was unchanged, but peak postmeal (185 ± 10 vs 166 ± 9 mg/dL, p = .003) and 3-hour glucose AUC (469 ± 23 vs 428 ± 19, p = .001) declined. Matsuda index improved (3.1 ± 0.5 vs 3.8 ± 0.5, p = .03), and corrected insulin response at 30 minutes was unchanged (0.6 ± 0.1 vs 0.5 ± 0.5, p = .49). There was a trend toward improved postmeal reactive hyperemia index (baseline vs resveratrol postmeal delta -0.4 ± 0.2 vs 0.2 ± 0.3, p = .06). Weight, blood pressure, and lipids were unchanged. CONCLUSIONS: At doses between 1 and 2 g/day, resveratrol improves insulin sensitivity and postmeal plasma glucose in subjects with IGT. These preliminary findings support the conduct of larger studies to further investigate the effects of resveratrol on metabolism and vascular function.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".