Can dietary fructans lower serum glucose?
Bibliographic record
Abstract
BACKGROUND: Convincing evidence indicates that the consumption of inulin-type fructans, inulin, and oligofructose has beneficial effects on blood glucose changes in animal models, although data in humans have been considered equivocal. As such, a systematic review of available literature on humans was conducted to evaluate the effectiveness of dietary inulin-type fructans on serum glucose. METHODS: Thirteen eligible randomized controlled trials (RCT), published from 1984 to 2009, were identified using a comprehensive search strategy involving the PubMed, Medline, and Cochrane Library databases. Exclusion criteria, such as the absence of a control group, lack of information on the quantity of inulin-type fructans used, and lack of glucose values at outcome, were established. RESULTS: Upon review, only four of the 13 trials (31%) showed a decrease in serum glucose concentration and only one of these was statistically significant. The remaining nine trials showed no significant changes in serum glucose concentration. CONCLUSION: Based on the present systematic review, it does not appear that inulin-type fructans have a significant lowering effect on serum glucose in humans. More RCT are needed to determine whether inulin-type fructans, inulin, and oligofructose have beneficial effects on blood glucose in humans.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| 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".