Effects of inulin fibre Supplementation on Serum Glucose and Lipid Concentration in Patients with Type 2 Diabetes
Bibliographic record
Abstract
Individuals who develop type 2 diabetes increase their chances of developing other health concerns such as cardiovascular disease. Soluble fibre has been shown to have positive effects on serum lipid and glucose levels. Inulin is a type of soluble fibre whose effects on serum lipid and glucose levels in individuals with type 2 diabetes are inconclusive due to the few studies that have been conducted. This study examined the effects of daily intake of 10 g of inulin-based fibre. This study included 36 individuals diagnosed with type 2 diabetes. Using a randomized, double-blind design patients consumed 10 g of either an inulin fibre supplement or xylitol as a placebo for 12-weeks. Compliance, expressed as the proportion of supplements not returned, was near 100% for both treatments. Inulin supplementation did not significantly affect fasting concentrations of serum total cholesterol, HDL cholesterol, LDL cholesterol, serum triglycerides, serum glucose, or hemoglobin A1c values. These results indicate that daily consumption of 10 g of inulin for 12 weeks does not affect serum lipid and glucose levels in patients with type 2 diabetes.The significant finding(s) of the Study: Short term supplementation of inulin is not effective in changing serum glucose and lipid profiles among those with type 2 diabetes.The study adds: Inulin supplementation on a short term may not be needed or effective in changing serum glucose and lipid profiles among individuals with well managed diabetes.
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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 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".