The ability of exercise to meaningfully improve glucose tolerance in people living with prediabetes: A meta‐analysis
Bibliographic record
Abstract
BACKGROUND: Individuals with prediabetes are likely to progress to Type 2 diabetes. Although exercise training is an established method to improve glycemic control, the degree to which this translates into meaningful improvements, particularly in individuals with prediabetes, is unclear. The purpose of this meta-analysis was to investigate the ability of exercise training to improve 2-hour glucose tolerance beyond the smallest worthwhile difference in individuals with prediabetes. It was hypothesized that the majority of implemented exercise programs designed for individuals with prediabetes would not result in meaningful improvements in glucose tolerance. METHODS: Searches were performed in MEDLINE, The Cumulative Index to Nursing and Allied Health Literature, SPORTDiscus, and the Cochrane Library. Included studies reported glucose tolerance using a 2-hour oral glucose tolerance test at baseline and post-intervention; implemented an exercise program lasting at least 12 weeks; and included adults living with prediabetes. Mean effect summaries were determined using random-effects models. Magnitude-based inference statistic was used to estimate the likelihood that observed changes in glucose tolerance were meaningful to patients. RESULTS: Nine articles were included in the meta-analysis, producing 12 independent exercise interventions. The interventions led to an average improvement in glucose tolerance of 5.9% (95% confidence interval: 3.7%-8.0%). Seven (58%) exercise interventions were deemed likely to benefit patients, whereas five (42%) had trivial or unclear findings. CONCLUSION: While exercise intervention led to statistically significant improvements in 2-hour glucose tolerance, the benefit for individuals living with prediabetes remains unclear. Further research is needed to delineate optimal prescription parameters for generating meaningful benefits in glucose tolerance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.019 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.060 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".