Respiratory characteristics in children with spinal muscular atrophy type 1 receiving nusinersen
Bibliographic record
Abstract
BACKGROUND: Spinal muscular atrophy type 1 (SMA1) is a neuromuscular disorder with a natural history of chronic respiratory failure and death during infancy without ventilation. Recently, disease-modifying therapies such as nusinersen have improved disease trajectory. However, objective data on the trajectory of polysomnography outcomes, the relationship between motor scores and respiratory parameters, respiratory technology dependence and healthcare utilization in children with SMA1 remain to be elucidated. METHODS: This was a retrospective observational study of children with SMA1 receiving nusinersen between October 2016 and February 2021 at two tertiary care hospitals in Canada. Baseline polysomnography data, motor scores, respiratory technology, and unanticipated healthcare utilization were examined. RESULTS: Eleven children (five females, two SMN2 copies each) were included. Median (interquartile range [IQR]) age at diagnosis was 3.6 (2.8-5.0) months and age at diagnostic polysomnogram following nusinersen initiation was 9.4 (5.3-14.0) months. Nusinersen was initiated at a median (IQR) age of 5.4 (3.4-7.6) months and 8/11 children had respiratory symptoms at that time. Diagnostic polysomnography data showed a median (IQR) central apnea-hypopnea index (AHI) of 4.1 (1.8-10.0) and obstructive AHI of 2.2 (0-8.0) events/h. We observed an inverse relationship between motor scores and central apnea-hypopnea indices. All children required ventilatory support at the end of the study period. CONCLUSION: This study showed abnormal polysomnography parameters and need for ventilation despite nusinersen suggesting ongoing need for regular monitoring with polysomnography. Understanding the respiratory disease trajectory of children undergoing treatment with nusinersen will inform decision-making regarding optimal timing of ventilatory support initiation.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".