Update on Body Composition and Bone Density in Children with Prader-Willi Syndrome
Bibliographic record
Abstract
AIM: To compare body composition in children with Prader-Willi syndrome (PWS) not naïve to growth hormone (GH) with obese and lean controls. METHODS: Participants included 12 children with PWS, 12 children with obesity (body fat percentage >95th percentile for age and sex) and 12 lean children (body fat percentage <85th percentile for age and sex) matched by age and height. Fat mass, lean mass, bone mineral content (BMC), bone mineral density (BMD) and BMD z-score for total body, hips and lumbar spine were obtained through dual X-ray absorptiometry. RESULTS: PWS had higher fat percentage in the legs (p = 0.04) but similar leg fat mass (p = 1.00) compared to obese. PWS exhibited lower lean mass in the body (p = 0.04) and legs (p = 0.02) than obese, but similar to lean (p = 1.00 and p = 0.89, respectively). PWS had lower hip BMC (p < 0.01), BMD (p < 0.01) and BMD z-score (p < 0.01) compared to obese but similar to lean. No other differences were found between PWS and obese (p > 0.05 for all). CONCLUSIONS: Children with PWS not naïve to GH present differences in fat and lean mass distribution compared to obese controls. BMC and BMD appear unaffected by PWS, except at the hips.
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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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".