Breath stacking in children with neuromuscular disorders
Bibliographic record
Abstract
Respiratory muscle weakness in neuromuscular disorders (NMD) can lead to shallow breathing and respiratory insufficiency over time. Children with NMD often cannot perform maneuvers to recruit lung volume. In adults, breath stacking with a mask and one-way valve can achieve significantly increased lung volumes. To evaluate involuntary breath stacking (IBS) in NMD, we studied 23 children of whom 15 were cognitively aware and able to communicate verbally. For IBS, a one-way valve and pneumotachograph were attached to a face mask. Tidal volumes (Vt) and minute ventilation (VE ) were calculated from airflow over 30 sec before and after 15 sec of expiratory valve closure. Six cooperative male subjects with Duchenne muscular dystrophy (DMD) participated in a subsequent comparison of IBS with voluntary breath stacking (VBS) and supported breath stacking (SBS). The average Vt in those studied with IBS was 277 ml (range 29-598 ml). The average increase in volume by stacking was 599 ml (range -140 to 2,916 ml) above Vt . The average number of stacked breaths was 4.5 (range 0-17). VE increased on average by 18% after stacking (P < 0.05, paired t-test). Oxygen saturation did not change after stacking. Four of the 23 children did not breath stack. Compared to IBS, VBS achieved similar volumes in the six subjects with DMD but SBS was more successful in those with greatest muscle weakness. IBS may achieve breath volumes of approximately three times Vt and may be particularly useful in non-cooperative subjects with milder degrees of respiratory muscle weakness.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".