Lifestyle Therapy for the Treatment of Youth with Type 2 Diabetes
Bibliographic record
Abstract
Type 2 diabetes (T2D) in youth is a relatively novel condition facing paediatric health care providers. Few experimental trials exist to guide clinical management in this population. Supporting and prescribing modifiable lifestyle behaviours is cornerstone in the management of T2D in adults. Clinical trials in obese adolescents suggest that intensive lifestyle interventions that include both dietary changes and increased physical activity elicit clinically meaningful reductions in weight and improve cardiovascular risk profiles. Observational studies in youth with T2D suggest that better diet quality and increased physical activity are associated with better metabolic control; however, the limited experimental data available does not support these observations. Trials evaluating lifestyle monotherapy for the treatment of hyperglycaemia in youth with T2D do not exist, and the only study evaluating combined lifestyle and pharmacologic therapy did not show additional benefit over pharmacologic treatment with metformin alone. Physiological and psychosocial differences between youth and adults with T2D likely contribute to the differences in the effectiveness of lifestyle therapy for improving glycaemic control. The current review describes these topics in detail and provides recommendations for paediatric health care providers for the promotion of lifestyle therapy for the management of hyperglycaemia and cardiovascular risk factors for youth with T2DM.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".