<i>Body Composition and Resting Energy Expenditure of Individuals</i>With Duchenne and Becker Muscular Dystrophy
Bibliographic record
Abstract
PURPOSE: The relationship between body composition and resting energy expenditure (REE) was investigated in two boys and two men with Duchenne muscular dystrophy (DMD) (ages 11 to 22.4 years) and two boys with Becker muscular dystrophy (BMD) (ages 7.75 and 13.75 years). METHODS: The REE was assessed by indirect calorimetry; body composition indices (weight, height, skinfolds, and mid-arm circumference) were measured using standardized techniques and compared with healthy reference data. RESULTS: Those with DMD had reduced corrected mid-upper-arm muscle area (C-MUMA) in comparison with healthy peers, and approximately twice the subcutaneous fat levels of subjects with BMD and healthy peers. Boys with BMD had remarkably lower muscle status than did boys with DMD and healthy peers. In both groups, REE was lower than in healthy peers; REE was associated with body weight (r=0.85), height (r=0.92), mid-upper arm fat area (MUFA) (r=0.97), and C-MUMA (r=0.65). CONCLUSIONS: Individuals with muscular dystrophy (MD) exhibit considerable disease-specific alterations in body composition. The REE had a stronger relationship with growth (weight and height) and subcutaneous body fat composition and a weaker association with C-MUMA. Understanding the effect of MD on body composition and REE will allow dietitians to individualize energy recommendations.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".