The Supraglottic Effect of a Reduction in Expiratory Mask Pressure During Continuous Positive Airway Pressure
Bibliographic record
Abstract
STUDY OBJECTIVES: Patients with obstructive sleep apnea may have difficulty exhaling against positive pressure, hence limiting their acceptance of continuous positive airway pressure (CPAP). C-Flex is designed to improve comfort by reducing pressure in the mask during expiration proportionally to expiratory airflow (3 settings correspond to increasing pressure changes). When patients use CPAP, nasal resistance determines how much higher supraglottic pressure is than mask pressure. We hypothesized that increased nasal resistance results in increased expiratory supraglottic pressure swings that could be mitigated by the effects of C-Flex on mask pressure. DESIGN: Cohort study. SETTING: Sleep center. PARTICIPANTS: Seventeen patients with obstructive sleep apnea/hypopnea syndrome and a mechanical model of the upper airway. INTERVENTIONS: In patients on fixed CPAP, CPAP with different C-Flex levels was applied multiple times during the night. In the model, 2 different respiratory patterns and resistances were tested. MEASUREMENTS AND RESULTS: Airflow, expiratory mask, and supraglottic pressures were measured on CPAP and on C-Flex. Swings in pressure during expiration were determined. On CPAP, higher nasal resistance produced greater expiratory pressure swings in the supraglottis in the patients and in the model, as expected. C-Flex 3 produced expiratory drops in mask pressure (range -0.03 to -2.49 cm H(2)O) but mitigated the expiratory pressure rise in the supraglottis only during a sinusoidal respiratory pattern in the model. CONCLUSIONS: Expiratory changes in mask pressure induced by C-Flex did not uniformly transmit to the supraglottis in either patients with obstructive sleep apnea on CPAP or in a mechanical model of the upper airway with fixed resistance. Data suggest that the observed lack of expiratory drop in supraglottic pressure swings is related to dynamics of the C-Flex algorithm.
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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 | 0.001 | 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 | 0.000 |
| 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".