Mechanical insufflation-exsufflation use in neuromuscular disease: a single centre cohort study
Bibliographic record
Abstract
Introduction Mechanical insufflation-exsufflation (MIE) is a commonly used therapy to augment secretion clearance in individuals with neuromuscular disease. There are no clear evidence-based guidelines on the settings that should be used in different diagnostic groups and how they should be titrated. We report on the settings used in the largest cohort of individuals using domiciliary MIE in the literature. Methods A retrospective observational study reporting on all individuals initiated on MIE for long-term domiciliary use at our centre, 2013–2019. Results This study reports on 359 adults established on domiciliary MIE. The most common diagnostic groups were congenital neuromuscular disease (26%), spinal cord injury (23%) and amyotrophic lateral sclerosis (23%). Median age at initiation was 55 years. Median (IQR) insufflation pressure was 35 (30–40) cm H 2 O and exsufflation pressure was 45 (40–50) cm H 2 O. Inspiratory time was 2.5 (2.3–2.8) s, expiratory time was 2.7 (2.3–2.8) s, and pause between expiration and inspiration was 2.0 (1.2–2.0) s. Median (IQR) survival following the initiation of MIE was 66 (54–78) months. Increasing age and amyotrophic lateral sclerosis were significantly associated with shorter life expectancy, while the delivery of MIE via oronasal interface compared with tracheostomy was associated with longer life expectancy. Conclusion This is the largest reported cohort of adults using domiciliary MIE. The most common groups using MIE were congenital neuromuscular disease, spinal cord injury patients and amyotrophic lateral sclerosis. The range of prescribed settings is narrow, reflecting the limited evidence base in this field and the need to better understand optimal targets for titration of different MIE settings.
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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 | 0.007 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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 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".