Exercise lowers postprandial glucose but not fasting glucose in type 2 diabetes: a meta‐analysis of studies using continuous glucose monitoring
Bibliographic record
Abstract
Exercise has repeatedly been shown to improve glycemic control as assessed by glycated hemoglobin. However, changes in glycated hemoglobin do not provide information regarding which aspects of glycemic control have been altered. The purpose of this systematic review was to examine the effect of exercise as assessed by continuous glucose monitoring systems (CGMS) in type 2 diabetes. Databases (PubMed, Medline, EMBASE) were searched up to February 2013. Eligible studies had participants with type 2 diabetes complete standardized exercise protocols and used CGMS to measure changes in glycemic control. Randomized controlled trials, crossover trials and studies with pre-post designs were included. Average glucose concentration, daily time spent in hyperglycemia or hypoglycemia, and fasting glucose concentration were compared between exercise and control conditions. Eleven studies met the inclusion criteria and were included in the review. Eight studies had short-term (≤2 weeks) exercise interventions, whereas three studies had a longer-term intervention (all >2 months). The types of exercises utilized included aerobic, resistance and a combination of the two. The eight short-term studies were included in quantitative analysis. Exercise significantly decreased average glucose concentrations (-0.8 mmol/L, p < 0.01) and daily time spent in hyperglycemia (-129 minutes, p < 0.01), but did not significantly affect daily time spent in hypoglycemia (-3 minutes, p = 0.47) or fasting glucose (-0.3 mmol/L, p = 0.13). The four randomized crossover trials had similar findings compared to studies with pre-post designs. Exercise consistently reduced average glucose concentrations and time spent in hyperglycemia despite not significantly affecting outcomes such as fasting glucose and hypoglycemia.
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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 | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.033 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".