A prospective, multi-center, observational study of the safety, tolerability and effectiveness of Nusinersen in adult patients with spinal muscular atrophy
Bibliographic record
Abstract
Nusinersen, an antisense oligonucleotide, modulates pre-mRNA splicing to produce full length survival motor neuron protein in spinal muscular atrophy (SMA). It was approved in the US for SMA in all ages based on evidence in children. In adults, studies of nusinersen rely on real-world observational data and show stability or small improvements over time. We performed a prospective, 30 month longitudinal, observational multi-center study of adults initiating nusinersen with SMA types II/III to examine its safety, tolerability, and effectiveness. 43 participants (20 female; 14 ambulatory; 3, 17, and 23 with 2, 3, and ≥4 SMN2 copies, respectively), mean (SD) age 37.1 (11.9) years) enrolled and completed baseline assessments. Serial assessments over 30 months showed small but not significant improvements in the six minute walk test (16.1 m), Revised Upper Limb Module (0.7), Revised Hammersmith Scale (0.8), maximal inspiratory (-2.6 cm H20) and expiratory pressure (12.3 cm H20). Muscle strength and forced vital capacity did not change. The patient reported outcome Total SMA-HI improved (-11 (95% CI: -17,-5); p < 0.001)). No new safety effects were identified. This study of nusinersen in adults with SMA demonstrates stability over time in contrast to the expected decline in untreated patients, with a favorable safety profile.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".