Height, weight, and body mass index trajectories and their correlation with functional outcome assessments in boys with Duchenne muscular dystrophy
Bibliographic record
Abstract
AIM: To examine the factors influencing height, weight, and body mass index (BMI) z-scores, and the relationship between them and motor performance, in boys with Duchenne muscular dystrophy (DMD). METHOD: This was a randomized, double-blind, parallel group trial involving 32 study sites across five countries. Height, weight, BMI z-scores, and clinical outcome assessments (COAs)-rise from supine velocity, 10-m walk/run velocity, NorthStar Ambulatory Assessment, and 6-minute walk test-were analysed in 4-year-old to 7-year-old boys with DMD randomized to 0.75 mg/kg/day prednisone, 0.75 mg/kg/day intermittent prednisone, or 0.90 mg/kg/day deflazacort in the FOR-DMD study. Trajectories were modelled using a linear mixed-effects model and correlations were explored through Spearman's partial correlations. RESULTS: In 194 boys with DMD, higher height at glucocorticoid initiation was associated with slower growth (p < 0.001) and older age was associated with increased weight gain (p = 0.001). Glucocorticoid type and regimen influenced height and weight trajectories but not BMI. Changes in height and weight z-scores were negatively correlated with COAs (p < 0.05 in all cases). Correlations were weak 3 years after glucocorticoid initiation and moderate after 5 years (closer to the age of loss of ambulation). INTERPRETATION: Changes in anthropometric measures after glucocorticoid initiation are associated with COA performance and larger correlations closer to the age of loss of ambulation. This emphasizes the need for weight management strategies and discussions that support treatment.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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".