Pharmacological Approaches for Management of Child and Adolescent Obesity
Bibliographic record
Abstract
UNLABELLED: Overweight and obesity among children and adolescents continue to be a global public health epidemic. Current national data on childhood and adolescent obesity show alarming statistics of overweight and obese children and adolescents. This epidemic runs across various continents and affects various ethnic populations. The current weight management practices involve dietary modification, behavioral change therapies involving exercise, pharmacological therapy and surgical intervention. The purpose of this current review is to focus on pharmacological therapy i.e. role of sibutramine and orlistat in childhood and adolescent weight management. An open search of PUBMED database was made with search key words such as orlistat or sibutramine or pharmacological approaches and child obesity and adolescent obesity. This yielded a total of 20 articles. All of these articles have been summarized in the current review. Sibutramine functions by promoting satiety and increases energy expenditure by inhibiting reuptake of noradrenaline and serotonin. Most of the studies, reviews and trials conducted using sibutramine among adolescents and children show limited short-term efficacy. The long-term effects of sibutramine use are not yet studied due to the severity of its side-effects profile. Orlistat was approved by Food and Drug Administration for adolescent weight reduction. Despite its approval, it has a limited role in adolescent and pediatric obesity reduction due to the purported malabsorption of fat soluble vitamins and its side-effect profile. Obesity and adolescent weight management in present times mainly deals with dietary modification with superadded behavioral therapies promoting exercise. There is insufficient evidence as of now if these alone would cause adequate weight reduction and weight maintenance. Pharmacotherapy i.e use of drugs like sibutramine and orlistat has a limited role in the current fight against childhood and adolescent obesity. Extreme side-effects, close monitoring and lack of long-term studies involving these drugs, suggest questionable efficacy in current times. Future research studies involving pharmacological agents need to not only have immense scientific rigor during preliminary analyses but should also translate their efficacy in practical and clinical settings. KEYWORDS: Obesity; Overweight; Adolescents; Pharmacological; sibutramine; Orlistat.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".