B.07 Review of patients with Spinal Muscular Atrophy treated with Nusinersen in Ontario
Bibliographic record
Abstract
Background: Spinal Muscular Atrophy (SMA) is an autosomal recessive neurodegenerative disease. In June 2017, Health Canada approved Nusinersen, currently the only available drug for SMA. Since 2016, patients in Ontario have been treated clinically with Nusinersen through different access programs. Methods: Retrospective case series of patients with SMA treated clinically with Nusinersen in Ontario, describing clinical characteristics and logistics of intrathecal Nusinersen administration. Results: Twenty patients have been treated across four centres. To date, we have reviewed 8 cases at one centre (seven SMA Type I, one SMA Type II). Age at first dose ranged from 3-156 months and disease duration 9-166 months. Patients had received 4-7 doses at last evaluation. Three patients with scoliosis (2 with spinal rods) required fluoroscopy-guided radiologist administration, and 4 required general anesthesia. No complications/adverse events were reported. At last follow up, 5/8 families reported improved daily activities. Of 5 patients with baseline and follow up motor function testing, 3 demonstrated improved scores. One patient died due to respiratory decline at age 9 months, despite improved motor outcome scores. Conclusions: We describe the first Canadian post-marketing experience with Nusinersen. Timely dissemination of this information is needed to guide clinicians, hospital administrators, and policy-makers.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".