Effects of Metformin Monotherapy on Metabolic Parameters in Japanese Patients With Type 2 Diabetes
Bibliographic record
Abstract
Background: Although metformin is widely used as the foundation therapy for patients with type 2 diabetes, effects of metformin monotherapy on metabolic parameters have not been sufficiently elucidated. Methods: We retrospectively picked up type 2 diabetic patients who had been treated by the first metformin monotherapy for more than 3 months, at National Center for Global Health and Medicine between January 2015 and October 2018. Results: Twenty-two patients were eligible. Systolic blood pressure, plasma glucose, HbA1c, low-density lipoprotein-cholesterol (LDL-C), aspartate transaminase (AST), and alanine aminotransferase (ALT) were significantly reduced by the 3-month metformin monotherapy. Further, we divided subjects into two groups with body mass index (BMI) of 25 or more and less than 25, and compared changes in metabolic parameter due to metformin monotherapy between BMI >= 25 and BMI = 25 group, and systolic blood pressure, AST and ALT tended to decrease only in BMI >= 25 group. Conclusions: The metformin monotherapy improved glycemic control regardless of the presence or absence of obesity. Interestingly, metformin improved body weight, blood pressure and liver function in only overweight patients with type 2 diabetes. J Endocrinol Metab. 2019;9(1-2):18-21 doi: https://doi.org/10.14740/jem549
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".