Subject–ventilator synchrony during neural versus pneumatically triggered non-invasive helmet ventilation
Bibliographic record
Abstract
OBJECTIVE: Patient-ventilator synchrony during non-invasive pressure support ventilation with the helmet device is often compromised when conventional pneumatic triggering and cycling-off were used. A possible solution to this shortcoming is to replace the pneumatic triggering with neural triggering and cycling-off-using the diaphragm electrical activity (EA(di)). This signal is insensitive to leaks and to the compliance of the ventilator circuit. DESIGN: Randomized, single-blinded, experimental study. SETTING: University Hospital. PARTICIPANTS AND SUBJECTS: Seven healthy human volunteers. INTERVENTIONS: Pneumatic triggering and cycling-off were compared to neural triggering and cycling-off during NIV delivered with the helmet. MEASUREMENTS AND RESULTS: Triggering and cycling-off delays, wasted efforts, and breathing comfort were determined during restricted breathing efforts (<20% of voluntary maximum EA(di)) with various combinations of pressure support (PSV) (5, 10, 20 cm H(2)O) and respiratory rates (10, 20, 30 breath/min). During pneumatic triggering and cycling-off, the subject-ventilator synchrony was progressively more impaired with increasing respiratory rate and levels of PSV (p < 0.001). During neural triggering and cycling-off, effect of increasing respiratory rate and levels of PSV on subject-ventilator synchrony was minimal. Breathing comfort was higher during neural triggering than during pneumatic triggering (p < 0.001). CONCLUSIONS: The present study demonstrates in healthy subjects that subject-ventilator synchrony, trigger effort, and breathing comfort with a helmet interface are considerably less impaired during increasing levels of PSV and respiratory rates with neural triggering and cycling-off, compared to conventional pneumatic triggering and cycling-off.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".