Rare sugars and their health effects in humans: a systematic review and narrative synthesis of the evidence from human trials
Bibliographic record
Abstract
CONTEXT: Rare sugars are monosaccharides and disaccharides (found in small quantities in nature) that have slight differences in their chemical structure compared with traditional sugars. Little is known about their unique physiological and cardiometabolic effects in humans. OBJECTIVE: The objective of this study was to conduct a systematic review and synthesis of controlled intervention studies of rare sugars in humans, using PRISMA guidelines. DATA SOURCES: MEDLINE and EMBASE were searched through October 1, 2020. Studies included both post-prandial (acute) and longer-term (≥1 week duration) human feeding studies that examined the effect of rare sugars (including allulose, arabinose, tagatose, trehalose, and isomaltulose) on cardiometabolic and physiological risk factors. DATA EXTRACTION: In all, 50 studies in humans focusing on the 5 selected rare sugars were found. A narrative synthesis of the selected literature was conducted, without formal quality assessment or quantitative synthesis. DATA SYNTHESIS: The narrative summary included the food source of each rare sugar, its effect in humans, and the possible mechanism of effect. Overall, these rare sugars were found to offer both short- and long-term benefits for glycemic control and weight loss, with effects differing between healthy individuals, overweight/obese individuals, and those with type 2 diabetes. Most studies were of small size and there was a lack of large randomized controlled trials that could confirm the beneficial effects of these rare sugars. CONCLUSION: Rare sugars could offer an opportunity for commercialization as an alternative sweetener, especially for those who are at high cardiometabolic risk. SYSTEMATIC REVIEW REGISTRATION: OSF registration no. 10.17605/OSF.IO/FW43D.
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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 | 0.027 | 0.105 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.011 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".