High-carbohydrate–low-glycaemic index dietary advice improves glucose disposition index in subjects with impaired glucose tolerance
Why this work is in the frame
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Bibliographic record
Abstract
Controversy exists about the optimal amount and source of dietary carbohydrate for managing insulin resistance. Therefore, we compared the effects on insulin sensitivity (S I ), pancreatic responsivity (AIR glu ) and glucose disposition index (DI=SI×AIRglu) of dietary advice aimed at reducing the amount or altering the source of dietary carbohydrate in subjects with impaired glucose tolerance (IGT). Subjects were randomized to high-carbohydrate–high-glycaemic index (GI) (high-GI, n 11), high-carbohydrate–low-GI (low-GI, n 13), or low-carbohydrate–high-monounsaturated fat (MUFA, n 11) dietary advice, with S I , AIR glu and DI measured using a frequently sampled, intravenous glucose tolerance test before and after 4 months treatment. Carbohydrate and fat intakes and diet GI, respectively, were: high-GI, 53 %, 28 %, 83; low-GI, 55 %, 25 %, 76; MUFA, 47 %, 35 %, 82. Weight changes on each diet differed significantly from each other: high-GI, -0·49 (SEM 0·29) KG; LOW-GI, -0·19 (sem 0·40) kg; MUFA +0·27 (sem 0·45) kg. Blood lipids did not change, but glycated haemoglobin increased significantly on MUFA, 0·02 (sem 0·11) %, relative to low-GI, -0·19 (sem 0·08) %, and high-GI, -0·13 (sem 0·14) %. Diastolic blood pressure fell by 8 mmHg on low-GI relative to MUFA ( P =0·038). Although S I and AIR glu did not change significantly, DI, a measure of the ability of β-cells to overcome insulin resistance by increasing insulin secretion, increased on low-GI by >50 % ( P =0·02). After adjusting for baseline values, the increase in DI on low-GI, 0·17 (sem 0·07), was significantly greater than those on MUFA, -0·09 (sem 0·08) and high-GI, -0·03 (sem 0·02) ( P =0·019). Thus, the long-term effects of altering the source of dietary carbohydrate differ from those of altering the amount. High-carbohydrate–low-GI dietary advice improved β -cell function in subjects with IGT, and may, therefore, be useful in the management of IGT.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it