Physical activity versus metformin for increasing insulin sensitivity in children and adolescents at-risk for type 2 diabetes
Bibliographic record
Abstract
Global rates of type 2 diabetes (T2D) among children and adolescents are steadily rising. As such, an increasing amount of attention and research has begun to focus on strategies to prevent this chronic and burdensome disease in pediatric populations. The purpose of this article is to briefly review current evidence pertaining to the effectiveness of physical activity versus metformin in improving insulin sensitivity of children at-risk (ie, obese and/or insulin resistant) for developing T2D. Potential barriers to each preventative intervention will also be discussed. Physical activity, both aerobic and resistance, has demonstrated effectiveness in a moderate number of demographically diverse pediatric studies. However, the pediatric population is already alarmingly sedentary with barriers such as lack of motivation, social stigma and discomfort presenting a challenge. A small number of studies have demonstrated the beneficial effects of metformin in children and adolescents for improved insulin sensitivity. However, longer and larger studies are required to confirm these findings and elucidate upon the long-term safety and efficacy of this pharmaceutical in pediatric populations. While no head-to-head studies examining physical activity and metformin exist in pediatric populations and more research is needed, current evidence seems to favour the use of physical activity given the larger quantity of studies and generalizability of its beneficial effects. Thus, physical activity should be emphasized in clinical and public health practice when targeting at-risk children and adolescents to prevent a T2D diagnosis.
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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 | 0.001 | 0.001 |
| 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".