Lung volume recruitment improves volitional airway clearance in amyotrophic lateral sclerosis
Bibliographic record
Abstract
INTRODUCTION/AIMS: In this study we evaluated the effects of lung volume recruitment treatment (LVR), a low-tech, low-cost, manual "breath-stacking" technique used to help people cough with enough force to clear their airways, thereby reducing the risk of aspiration and choking, on five volitional airway clearance and protection behaviors used by people living with amyotrophic lateral sclerosis (PwALS). METHODS: Using a repeated-measures cross-over design, 29 PwALS performed five volitional airway clearance and protection behaviors in LVR treatment and in no-treatment, control conditions. Peak cough flow (PCF) was used to measure maximum expiratory rate during forced expiration, throat clearing, hawking, post-swallow coughing, and the supraglottic swallowing maneuver. Comparisons were made as a function of condition (treatment or control) and three time-points (pretreatment, and 15 and 30 minutes posttreatment). RESULTS: LVR treatment had a significant positive effect on maximum expiratory rates during all tested airway clearance and protection behaviors. Increased PCF values lasted for up to 30 minutes post-LVR for all tested behaviors in the treatment condition. DISCUSSION: We found that LVR treatment could increase control over airway clearance in PwALS, as well as provide improved airway protection for up to 30 minutes, the duration of a typical meal. This study has implications for patient care. These include offering patients control over some of the most feared symptoms of ALS, particularly choking during activities of daily living, and enhanced ALS respiratory care in low-resource settings. Findings may have implications for other neurodegenerative disorders in which dysphagia occurs with retained sensory function.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".