Dystrophin isoform deficiency and upper‐limb and respiratory function in Duchenne muscular dystrophy
Bibliographic record
Abstract
AIM: To investigate the associations between mutations expected to differentially affect Dp140 expression and long-term trajectories of respiratory and upper-limb motor outcomes in Duchenne muscular dystrophy (DMD). METHOD: In a retrospective analysis of population-based longitudinal data from three real-world and natural history data sources, individuals with DMD aged 5 years to 18 years were subdivided according to the predicted effects of the participants' DMD mutation on dystrophin isoform expression (group 1, Dp427 absent, Dp140/Dp71 present; group 2, Dp427/Dp140 absent, Dp71 present). RESULTS: A total of 459 participants were studied, with upper-limb outcomes assessed in 71 (27 in group 1 and 44 in group 2) and forced vital capacity percentage predicted (%pred) assessed in 434 (224 in group 1 and 210 in group 2). Mean grip strength %pred was on average 7.1 percentage points lower in group 2 than in group 1 (p = 0.03). Mean pinch strength %pred was on average 9.2 percentage points lower in group 2 than in group 1 (p = 0.04). Mean forced vital capacity %pred was on average 4.3 percentage points lower in group 2 than in group 1 (p = 0.01). INTERPRETATION: In individuals with DMD, DMD mutations predicted to affect Dp140 expression were associated with more severe trajectories of respiratory and upper-limb motor outcomes.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".