Metformin for the Treatment of Type 2 Diabetes in Asian Adults: A Systematic Review
Bibliographic record
Abstract
Metformin is a cheap, orally administered, guideline recommended glucose-lowering drug (GLD), initiated as monotherapy in treatment naïve newly diagnosed type 2 diabetes (T2D), and in combination with other GLDs in T2D not controlled on metformin. The unique Asian T2D phenotype that is markedly different than Western population, and warrants T2D treatment approaches unique to the Asian population. However, the bulk of metformin literature is from Western population and may not be generalizable for Asians. The systematic review evaluated the efficacy and safety of metformin monotherapy and combination therapy in Asians. Literature on other GLDs recommended by the 2023 American Diabetes Association guidelines as add-on therapy to metformin were included from Asia. The systematic review concluded that metformin is effective and safe for long-term T2D control of T2D in Asians. Metformin monotherapy may be initiated and continued in treatment naïve Asian patients with T2D and/or obesity if the monotherapy is adequate for achieving glycemic control. Other GLDs may be added for better glycemic control for those who fail on monotherapy. Patients inadequately controlled on another first-line GLD can achieve glycemic control and target HbA1c of <7% by adding metformin in a once daily dose. The use of metformin reduces the risk of hypoglycemia, and its gastrointestinal side effects are mild and manageable in Asians.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".