Duchenne Muscular Dystrophy: Canadian Paediatric Neuromuscular Physicians Survey
Bibliographic record
Abstract
BACKGROUND: Duchenne muscular dystrophy (DMD) is the most common form of muscular dystrophy in childhood. METHOD: To assess the current care of paediatric DMD patients in Canada, a questionnaire was mailed to 17 physicians who were members of the Canadian paediatric neuromuscular group. Areas of enquiry included; 1) multidisciplinary team composition; 2) means of DMD diagnosis; 3) corticosteroid use; surveillance and management for: 4) orthopaedic, 5) respiratory and 6) cardiac complications and 7) health maintenance (nutrition & immunizations). RESULTS: Completed surveys were returned by 14/17 (82%) of physicians. Twelve respondents followed DMD patients. All centres had multidisciplinary teams, including respirology (11/12), child neurology or physiatry (11), physiotherapy (9), occupational therapy (9) and orthopaedic surgery (7). Deflazacort 0.9 mg/kg/d was used at all centres, which was continued after loss of independent ambulation (11), along with routine calcium and vitamin D supplementation (10). Night splints were prescribed at all centres. Routine surveillance studies included pulmonary function testing (11), sleep studies (10), EKG/echocardiogram (10), bone density (DEXA) scans (10), spine radiography (9), and dietician referral (4). CONCLUSION: Paediatric DMD patients are receiving relatively consistent care in multidisciplinary clinics across Canada, in accordance with recommended guidelines for DMD.
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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 | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".