Effects of Postmeal Exercise on Postprandial Glucose in People Treated with Metformin
Bibliographic record
Abstract
Postprandial hyperglycemia is associated with the development of macrovascular and microvascular diseases. Thus, there is a need for effective treatments that reduce postprandial hyperglycemia. Metformin is used clinically to reduce blood glucose, however, hyperglycemia is not always adequately controlled with metformin. It is currently unknown how the combination of metformin and postmeal exercise affects postprandial glucose. PURPOSE: Examine the effects of postmeal exercise on postprandial glucose in people being treated with metformin. METHODS: 2-hr area under the curve after a standardized breakfast meal and peak postprandial glucose, assessed with continuous glucose monitoring, were compared in sedentary versus postmeal exercise conditions in 6 people treated with metformin. Postmeal exercise began 30 minutes into the postprandial phase and consisted of 5 x 10 minutes bouts of treadmill walking at 60% maximal oxygen uptake. RESULTS: 2-hr area under the breakfast curve was 27% lower after postmeal exercise (sed: 1315 ± 299 vs. ex: 998 ± 235 mmol/L x 2 hr; p = 0.008). Peak glucose was 28% lower after postmeal exercise (sed: 11.8 ± 2.9 vs. ex: 8.9 ± 1. mmol/L; p = 0.01). Postmeal exercise lowered postprandial glucose levels below the current International Diabetes Federation postmeal recommendation of 8.8 mmol/L in 3 of 6 participants. CONCLUSION: Postmeal exercise resulted in postprandial glucose reduction in people being treated with metformin, and therefore may be a useful approach for managing postprandial hyperglycemia. Funded by the University of Georgia College of Education, Office of the Vice President for Research, and the Mary Ella Lunday Soule Scholarship.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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".