Emerging treatments for severe obesity in children and adolescents
Bibliographic record
Abstract
Severe obesity in childhood is increasing in prevalence and is associated with considerable morbidity. Studies into pediatric obesity have focused largely on interventions that do not necessarily target the unique biologic or psychological underpinnings for the weight gain in the individual child or adolescent. Outcomes show modest improvement and are of questionable benefit for patients with severe obesity. Although weight is a commonly used outcome, other psychological and metabolic parameters including normalization of physical activity and eating behaviors should be primary outcome goals. The durability of weight loss is often limited by physiologic systems that are evolutionarily designed to promote weight gain. Drug therapies for children are limited, as is their effect on weight and metabolism. Existing drugs that are incidentally found to cause weight loss through off-target effects are being actively investigated for obesity indications. Bariatric surgery results in the most significant weight reduction, but it is associated with potential morbidity and long term data are not available for adolescents undergoing this procedure. As understanding of the biologic and psychosocial contributors to eating behaviors and body weight regulation increases, multifaceted and targeted behavioral, pharmacological, and surgical treatment algorithms should be developed and applied to target the underlying pathways involved for the individual child or adolescent with severe obesity.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.005 | 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".