Carbohydrate and Fiber Recommendations for Individuals with Diabetes: A Quantitative Assessment and Meta-Analysis of the Evidence
Bibliographic record
Abstract
To review international nutrition recommendations with a special emphasis on carbohydrate and fiber, analyze clinical trial information, and provide an evidence-based recommendation for medical nutrition therapy for individuals with diabetes. Relevant articles were identified by a thorough review of the literature and the data tabulated. Fixed-effects meta-analyses techniques were used to obtain mean estimates of changes in outcome measures in response to diet interventions. Most international organizations recommend that diabetic individuals achieve and maintain a desirable body weight with a body mass index of </=25 kg/m(2). For diabetic subjects moderate carbohydrate, high fiber diets compared to moderate carbohydrate, low fiber diets are associated with significantly lower values for: postprandial plasma glucose, total and low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and triglycerides. High carbohydrate, high fiber diets compared to moderate carbohydrate, low fiber diets are associated with lower values for: fasting, postprandial and average plasma glucose; hemoglobin A(1c); total, LDL-cholesterol, HDL-cholesterol and triglycerides. Low glycemic index diets compared to high glycemic index diets are associated with lower fasting plasma glucose values and lower glycated protein values. Based on these analyses we recommend that the diabetic individual should be encouraged to achieve and maintain a desirable body weight and that the diet should provide these percentages of nutrients: carbohydrate, >/=55%; protein, 12-16%; fat, <30%; and monounsaturated fat, 12-15%. The diet should provide 25-50 g/day of dietary fiber (15-25 g/1000 kcal). Glycemic index information should be incorporated into exchanges and teaching material.
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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 | 0.091 | 0.176 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.039 |
| Bibliometrics | 0.018 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".