Association between neurodevelopmental impairments and motor function in Duchenne muscular dystrophy
Bibliographic record
Abstract
OBJECTIVE: We explored various prognostic factors of motor outcomes in corticosteroid-naive boys with Duchenne Muscular Dystrophy (DMD). METHODS: The associations between parent-reported neurodevelopmental concerns (speech delay, speech and language difficulties (SLD), and learning difficulties), DMD mutation location, and motor outcomes (6-minute walk distance (6MWD), North Star Ambulatory Assessment (NSAA) total score, 10-meter walk/run velocity, and rise from floor velocity) were studied in 196 corticosteroid-naive boys from ages 4 to less than 8 years. RESULTS: Participants with SLD walked 25.8 fewer meters in 6 minutes than those without SLD (p = 0.005) but did not demonstrate statistical differences in NSAA total score, 10-meter walk/run velocity, and rise from floor velocity. Participants with distal DMD mutations with learning difficulties walked 51.8 fewer meters in 6 minutes than those without learning difficulties (p = 0.0007). Participants with distal DMD mutations were slower on 10-meter walk/run velocity, and rise from floor velocity (p = 0.02) than those with proximal DMD mutations. Participants with distal DMD mutations, who reported speech delay or learning difficulties, were slower on rise from floor velocity (p = 0.04, p = 0.01) than those with proximal DMD mutations. The mean NSAA total score was lower in participants with learning difficulties than in those without (p = 0.004). INTERPRETATION: Corticosteroid-naive boys with DMD with distal DMD mutations may perform worse on some timed function tests, and that those with learning difficulties may perform worse on the NSAA. Pending confirmatory studies, our data underscore the importance of considering co-existing neurodevelopmental symptoms on motor outcome measures.
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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 | 0.002 |
| 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".