The Effect of an Expiratory Resistance Mask with Dead Space on Sleep, Acute Mountain Sickness, Cognition, and Ventilatory Acclimatization in Normobaric Hypoxia
Bibliographic record
Abstract
Abstract We examined the hypothesis that an expiratory resistance mask containing a small amount of dead space (ER/DS) would reduce the apnea–hypopnea index (AHI) during sleep, attenuate the severity of acute mountain sickness (AMS), and offset decrements in cognitive function compared with a sham mask. In a double-blinded, randomized, sham-controlled, crossover design, 19 volunteers were exposed to two nights of normobaric hypoxia (F I O 2 = 0.125), using a ER/DS mask (3.5 mm restrictive expiratory orifice; 125 mL DS volume) and sham mask (zero-flow resistance; 50 mL DS volume). Cognitive function, AMS, and ventilatory acclimatization were assessed before and after the 12-hour normobaric hypoxia exposure. Polysomnography was conducted during sleep. AHI was reduced using the ER/DS sleep mask compared with the sham (30.1 ± 23.9 events·hr −1 vs. 58.9 ± 34.4 events·hr −1 , respectively; p = 0.01). Likewise, oxygen desaturation index and headache severity were reduced (both p < 0.05). There were also benefits on limiting the hypoxia-induced reductions in select measures of reaction speed and attention ( p < 0.05). Our study indicates that a simple noninvasive and portable ER/DS mask resulted in reductions (49%) in AHI, and reduced headache severity and aspects of cognitive decline. The field applications of this ER/DS mask should be investigated before recommendations can be made to support its benefit for travel to high altitude.
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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 | 0.001 |
| 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) | 0.001 | 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 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".