Exercise in type 2 diabetes mellitus: A meta-analysis of the effects of exercise on glycemic control, body composition and physical fitness.
Bibliographic record
Abstract
The purpose of the study was to systematically review and quantify the effect of exercise interventions on HbAlc and body mass in type 2 diabetes. A literature search was conducted to find all controlled clinical trials in type 2 diabetic adults comparing an exercise intervention (≥8 weeks) to a non-exercise control. Weighted mean differences (WMD) and standardised mean differences (SMD) were used to calculate the size of the effect of exercise. Eleven aerobic training studies (average: 3.5 times/week for 18.6 weeks) and 2 resistance training studies (average: 10 exercises, 2.5 sets, 13 repetitions, 2.5 times/week for 15 weeks) met the inclusion criteria. In the first set of analyses, the effects of exercise on HbAlc and body mass were studied. Aerobic training interventions produced a significant decrease in HbAIc compared to control (WMD = -0.74, p = 0.00003). Improvements in HbAlc with resistance training were similar in size (WMD = -0.64, p = 0.05). Although the exercise groups lost a mean of 2.5 kilograms, their post-intervention body mass was not statistically different from the control groups' (SMD = 0.10 standard deviations (SD), p = 0.76). In the second set of analyses, aerobic training produced a 11% increase in VO 2 max compared to control (SMD = 0.49 SD, p = 0.003). When only intense aerobic interventions are considered (≥75% VO2 max) the post-intervention VO2 max was 30% higher than in the control group. Improvements in strength produced by resistance training were also significant (SMD = 1.00, p = 0.0001). In summary, exercise training resulted in statistically and clinically significant improvements in HbAIc without change in body mass compared to control. On the other hand, there is little information available from controlled clinical trials on the effect of exercise on other elements of body composition and physical fitness in type 2 diabetes.
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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 | 0.010 | 0.018 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.031 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 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".