Upper Airway Pressures in Snorers and Nonsnorers during Wakefulness and Sleep
Bibliographic record
Abstract
OBJECTIVE: To compare upper airway pressures in snorers and nonsnorers during sleep and wakefulness. DESIGN: Case series of snorers and nonsnoring controls. SETTING: Sleep clinic of a university hospital. METHODS: We used open catheters to measure differential nasopharyngeal and hypopharyngeal pressures in 8 nonapneic snorers with excessive daytime tiredness and 10 healthy nonsnoring controls. Measurements were performed during sleep (with the mouth taped to ensure exclusively nasal breathing) and wakefulness. When awake, the subjects were either seated (with the head neutral, flexed, extended, or rotated) or recumbent (dorsal and lateral positions). MAIN OUTCOME MEASURES: Comparison of pressures within the group as a function of body position and between the groups as a function of snoring. RESULTS: Differential nasal and pharyngeal pressures were similar in seated snorers and nonsnorers independently of head position. Assumption of recumbency resulted in significantly increased pharyngeal pressures in nonsnorers (26 +/- 18 Pa seated vs. 52 +/- 46 Pa recumbent, p < .05) and snorers (50 +/- 35 Pa seated vs. 93 +/- 38 recumbent, p < .01). The increase was higher in snorers than nonsnorers. During snoring, sleep differential pharyngeal pressures in snorers were markedly increased compared to quiet sleep (567 +/- 450 Pa during snoring epochs vs. 117 +/- 82 Pa during nonsnoring epochs, p < .01). CONCLUSIONS: Compared to nonsnorers, recumbent nonapneic snorers have elevated differential pharyngeal pressures indicative of increased upper airway resistance and reduced airway patency; this is present during wakefulness and sleep.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".