P.070 Delay to diagnosis of Duchenne muscular dystrophy
Bibliographic record
Abstract
Background: Duchenne muscular dystrophy (DMD) typically presents with painless weakness which may contribute to its delayed recognition. Methods: Retrospective chart review was performed for patients with DMD at CHEO over 15 years (2009-2023). Our data will later be combined with that from two other centers. Inclusion criteria: 1) confirmed DMD; 2) symptom onset <6 yo. Exclusion criteria: incomplete records or family history of DMD. Results: We identified 72 DMD patients. Total of N=49 were analyzed. Subjects were excluded for: incomplete data N=10 (e.g. diagnosis at another centre); symptom onset ≥6 yo (N=4); family history (N=9). First symptoms were reported at a mean age of 2.7 yo (range: 0-5.9 yo) with diagnosis at mean age of 5.2 yo (range: 0.5 to 9.6 yo), representing a mean delay of 2.5 years (range: 0-6.8 yrs). Initial symptoms included: weakness (61.2%), sports difficulty (61.2%), calf pseudohypertrophy (10.2%), language difficulties (8.2%) or muscle pain (2.0%). Learning disability was reported in 36 (73.5%) subjects with 7 (14.3%) having autistic spectrum disorder. Conclusions: The mean delay to diagnosis of patients followed at our centre was similar to the United Kingdom (MDSTARnet). We advocate for increased education to identify DMD earlier, particularly given emerging therapies for this disorder.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".