Short-Term Effects of Nonnutritive Sweetener (Sucralose and Saccharin) Consumption on Glycemic Control and Gut Microbiota in Patients With Type 2 Diabetes: Protocol for a Double-Blind, Randomized, Placebo-Controlled, Crossover Trial
Bibliographic record
Abstract
BACKGROUND: Nonnutritive sweeteners (NNSs) are widely used as sugar substitutes to help individuals with diabetes manage glycemic control. However, emerging evidence suggests that even low doses of NNSs, such as saccharin and sucralose, may adversely affect metabolic health by impairing glycemic regulation, potentially through alterations in the gut microbiota. In Malaysia, where gut microbiome research is still limited, particularly among individuals with type 2 diabetes mellitus (T2DM), further investigation is warranted to inform safe and evidence-based use of NNSs. OBJECTIVE: This study aims to evaluate the short-term effects of saccharin and sucralose consumption on glycemic control and gut microbiota composition in adults with T2DM. METHODS: This is a double-blind, randomized, placebo-controlled, crossover trial. A total of 33 adults with T2DM will consume sucralose (5 mg/kg body weight), saccharin (2 mg/kg body weight), or a placebo (calcium carbonate) in capsule form daily for 7 days per intervention arm, with a 4-week washout period. Data collection will include anthropometric measurements, biochemical assessments for glycemic control, dietary records, physical activity levels, and stool samples. The homeostatic model assessment for insulin resistance will be used to assess insulin sensitivity, while 16S rRNA V3-V4 region sequencing will be conducted to profile gut microbiota composition. RESULTS: Recruitment is planned to begin in January 2026 and is expected to conclude by September 2026, with study completion anticipated by March 2027. As of December 2025, no participants have been enrolled. CONCLUSIONS: This trial will contribute novel insights into the effects of short-term NNS consumption on glycemic control and gut microbiota composition in individuals with T2DM. These findings may support evidence-based recommendations for NNS use in diabetes management and enhance understanding of microbiome-diet interactions in an ethnically diverse Asian population. TRIAL REGISTRATION: ClinicalTrials.gov NCT07124585; https://clinicaltrials.gov/study/NCT07124585. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/82695.
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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 | 0.015 | 0.013 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.010 | 0.005 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.031 | 0.006 |
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".