An algorithm for discontinuing mechanical ventilation in boys with x-linked myotubular myopathy after positive response to gene therapy: the ASPIRO experience
Bibliographic record
Abstract
X-linked myotubular myopathy (XLMTM) is a rare, life-threatening congenital myopathy. Most (80%) children with XLMTM have profound muscle weakness and hypotonia at birth resulting in severe respiratory insufficiency, the inability to sit up, stand or walk, and early mortality. At birth, 85-90% of children with XLMTM require mechanical ventilation, with more than half requiring invasive ventilator support. Historically, ventilator-dependent children with neuromuscular-derived respiratory failure of this degree and nature, static or progressive, are not expected to achieve complete independence from mechanical ventilator support. In the ASPIRO clinical trial (NCT03199469), participants receiving a single intravenous dose of an investigational gene therapy (resamirigene bilparvovec) started showing significant improvements in daily hours of ventilation support compared with controls by 24 weeks post-dosing, and 16 of 24 dosed participants achieved ventilator independence between 14 and 97 weeks after dosing. At the time, there was no precedent or published guidance for weaning chronically ventilated children with congenital neuromuscular diseases off mechanical ventilation. When the first ASPIRO participants started showing dramatically improved respiratory function, the investigators initiated efforts to safely wean them off ventilator support, in parallel with primary protocol respiratory outcome measures. A group of experts in respiratory care and physiology and management of children with XLMTM developed an algorithm to safely wean children in the ASPIRO trial off mechanical ventilation as their respiratory muscle strength increased. The algorithm developed for this trial provides recommendations for assessing weaning readiness, a stepwise approach to weaning, and monitoring of children during and after the weaning process.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".