Duchenne Muscular Dystrophy Fatigue Trajectories
Bibliographic record
Abstract
INTRODUCTION: Children with Duchenne muscular dystrophy (DMD) are at risk of experiencing fatigue that negatively impacts their health-related quality of life (HRQoL). This study aimed to assess the association between fatigue and HRQoL, by examining fatigue trajectories over 48 weeks, and assessing factors associated with these fatigue trajectories. METHODS: The study sample consisted of 173 DMD subjects enrolled in a 48-week-long phase 2 clinical trial (NCT00592553) for a novel therapeutic who were between the ages of 5 and 16 years. RESULTS: = 0.47 for child self-report and 0.36 for parent proxy report) were significantly associated with one another. Three unique fatigue trajectories using Latent Class Growth Models were identified for child and parent proxy reported fatigue. The risk of being in the high fatigue group as compared to the low fatigue group increased by 24% with each year increase in age and also with decreasing walking distance, as reported by children and parent proxy, respectively. CONCLUSION: This study identified fatigue trajectories and risk factors associated with greater fatigue, helping clinicians and researchers identify the profile of fatigue in DMD children.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".