Health-related quality of life in children with Duchenne muscular dystrophy: a follow-up study
Bibliographic record
Abstract
Background: Improvement of health-related quality of life (HRQOL) is a major goal in chronic disease management and HRQOL has become an important outcome in clinical trials. Longitudinal data on HRQOL are needed to elucidate change over time and to assess effectiveness of interventions; such research is lacking in the paediatric Duchenne Muscular Dystrophy (DMD) population. Methods: We followed up participants from our initial HRQOL study in 2013 a year and a half later. Multidimensional generic and disease-specific measures from the Pediatric Quality of Life Inventory were used to assess HRQOL from child and parent perspectives. Mean changes in HRQOL were calculated. Results: Data collection is ongoing and currently, data from 16 families (out of the initial 98) are available. Preliminary results indicated that by both child and parent reports, there were declines in all domains of HRQOL except for social function, in which there was a slight improvement. Mean decline in HRQOL scores ranged from 1.6 to 8.6 for child reports; and 3.3 to 7.7 for parent reports. Conclusion: HRQOL of boys with DMD deteriorates over time. Our results may be helpful in interpreting patient reported outcomes in forthcoming clinical trials and determining minimally clinically important changes in this population.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".