Comparison of Metformin and Alogliptin Fixed-Dose Tablets Once a Morning Versus Once an Evening Using Continuous Glucose Monitoring (AMPM Study): An Open-Label Randomized Cross-Over Trial
Bibliographic record
Abstract
Background: The aim of the study is to compare the effect of metformin hydrochloride and alogliptin benzoate combination tablets medication once daily am/pm on blood glucose and investigate predictive factors for drug responses. Methods: This is a single-center, single-dose, open-label, randomized, two-treatment (once-daily, am and pm), two-sequence and two-period crossover study with a washout period of 1 day. Glycemic variability and control were assessed using the FreeStyle Libre Pro continuous glucose monitoring in terms of time spent in different glycemic ranges and low/high blood glucose indices (LBGI/HBGI), and compared between the dosing timing. Results: The average postprandial glucose in lunch and dinner in AM group were lower but not significant compared to PM group. There was no difference in average, time above range (TAR: > 180 mg/dL), time in range (TIR: 70 - 180 mg/dL), time below range (TBR: < 70 mg/dL), and area under curve (AUC) (AM0 - AM6, AM6 - PM0, PM0 - PM6, and PM6 - PM12) between treatments time (AM vs. PM). There was a significant strong negative correlation between high-density lipoprotein cholesterol (HDL-C) levels and changes of HBGI from AM to PM (r = -0.608), but HDL-C levels were not associated with LBGI. There was moderately strong correlation between evening type in chronotype and changes of HBGI from AM to PM (r = 0.592). Conclusions: These findings suggest that HDL-C levels and chronotype might modulate drug response, although there was no difference in average, TIR, TBR, TAR, and AUC between treatments timing in patients with type 2 diabetes (T2D). J Endocrinol Metab. 2021;11(1):8-13 doi: https://doi.org/10.14740/jem720
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".