The Influence of the Menstrual Cycle on Upper Airway Resistance and Breathing During Sleep
Bibliographic record
Abstract
STUDY OBJECTIVE: Female hormones, specifically progesterone, that peak in the luteal phase may play a significant role in protecting premenopausal women from sleep-disordered breathing. The influence of female hormones on upper airway resistance during sleep was investigated during the follicular and luteal phases of normal menstrual cycles. SETTING: Hospital-based sleep laboratory. DESIGN AND PARTICIPANTS: Healthy women with verified ovulatory cycles and without sleep complaints were recruited into the study. Sleep and upper airway resistance data (mean +/- SD) were collected on 2 nights from 11 women (21-49 years of age [28 +/- 9 years], body mass index of 22.8 +/- 3.6 kg/m2), once during the follicular phase (day 6-11) and once in the luteal phase (day 19-23) in random order. MEASUREMENTS AND RESULTS: Nasal resistance, standardized to a flow rate of 0.3 L/second, measured using posterior active rhinomanometry immediately prior to the sleep study, did not differ between the 2 phases. The respiratory disturbance index tended to be higher in the follicular phase than in the luteal phase and was above 5 per hour for 3 women in the follicular phase. Upper airway resistance, controlled for flow rate and body position, was calculated for 50 random breaths during wakefulness, stage 1, stage 2, slow-wave, and rapid eye movement sleep. During wake and stage 2 sleep, upper airway resistance was significantly higher in the follicular phase than in the luteal phase, as was the overall upper airway resistance combined for wake and across all sleep stages. Combining data from the 2 nights, compared to wake, upper airway resistance increased in stage 2, slow-wave, and rapid eye movement sleep. CONCLUSIONS: Within the menstrual cycle, upper airway resistance is lower in the luteal compared with the follicular phase.
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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) | 0.000 | 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".