Effect of Metformin on Different Non-Diabetes Related Conditions, a Special Focus on Malignant Conditions: Review of Literature
Bibliographic record
Abstract
Metformin has been proven to be one of the most safe and effective antihyperglycemic agents. Through more than six decades of metformin use, it became the most studied hypoglycemic agent; through these studies, it showed a marvelous non-glycemic related effect. These effects include modulation of different points of cancer timeline, weight reduction, cardiovascular health, thyroid diseases, polycystic ovaries disease and many other medical conditions. The aim of this review was to assess the effect of metformin on non-diabetes related medical diseases. We have examined the studies published in PubMed and summarized different randomized controlled trials, observational trials and review articles. This review has summarized most of the non-glycemic effects of metformin. Metformin has been solidly shown to be effective in weight control with certain medications, effective in neuroprotection, in endothelial health, in control of anti-HIV agent side effects and many other crucial health jeopardies. The effects in cancer timeline modulation have taken the biggest part, since it was the most studied area outside the diabetes field. Having mentioned all the above privileges, and in addition to the robust evidence in glycemic control, this consolidates the position of metformin as a first line agent in treatment of diabetes and pre-diabetes. Perhaps in the near future, we may see other indications to use metformin in non-diabetes patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".