The impact of macro- and micronutrients on metformin anti-diabetic activity: a systematic review
Bibliographic record
Abstract
Introduction: Type 2 Diabetes Mellitus (T2DM) affects over 537 million individuals worldwide, with cases expected to rise to 783 million by the year 2045. Metformin is the primary treatment, but its efficacy varies due to dietary influences. Growing evidence suggests that macro- and micronutrients interact with metformin, influencing its therapeutic effects. However, these interactions remain poorly understood. This review aims to bridge this knowledge gap by synthesizing recent findings on metformin-nutrient interactions to inform optimized therapeutic and dietary strategies. Objective: The objective of this systemic review is to investigate the impact of macro- and micronutrients on metformin anti-diabetic activity. Methods: This systematic review adheres to PRISMA guidelines, focusing on systematic reviews, meta-analyses, and experimental studies from PubMed, Scopus, and Web of Science. The research was carried out from September to October 2024. The studies were evaluated for quality using the GRADE tool and the risk of bias was assessed using the Cochrane tool. Results and conclusion: 132 research studies were identified and subjected to an eligibility assessment. After a careful evaluation, 33 studies were included in this systematic review. The Cochrane tool used for assessing the risk of bias revealed that 22 studies had a high risk of bias, while 24 studies failed to meet the GRADE criteria. Most of the studies showed homogeneity in their findings, with X2=85.7%>50%. It was concluded that high saturated fat intake reduces metformin’s effect alternatively, nutrients like leucine enhance metformin efficacy through mechanisms involving the AMPK pathway, promoting lipid oxidation and glycemic improvements. Micronutrients such as calcium, magnesium, and potassium play essential roles in glucose metabolism and insulin signaling. These minerals are absorbed through OCT1 transporters, the same transport pathway used by metformin for cellular uptake. Clinical trials have demonstrated that adequate dietary intake of these micronutrients stabilizes blood glucose levels when combined with metformin. In conclusion, it is suggested that dietary composition should be an integral component of T2DM management for patients on metformin therapy.
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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 | 0.011 | 0.045 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.012 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".