Genioglossus activity available via non-arousal mechanisms vs. that required for opening the airway in obstructive apnea patients
Bibliographic record
Abstract
It is generally believed that reflex recruitment of pharyngeal dilator muscles is insufficient to open the airway of obstructive apnea (OSA) patients once it is closed and, therefore, that arousal is required. Yet arousal promotes recurrence of obstruction. There is no information about how much dilator [genioglossus (GG)] activation is required to open the airway (GG Opening Threshold) or about the capacity of reflex mechanisms to increase dilator activity before/without arousal (Non-Arousal Activation). The relationship between these two variables is important for ventilatory stability. We measured both variables in 32 OSA patients (apnea-hypopnea index 74 ± 42 events/h). GG activity was monitored while patients were on optimal continuous positive airway pressure (CPAP). Zopiclone was administered to delay arousal. Maximum GG activity (GG(MAX)) and airway closing pressure (P(CRIT)) were measured. During stable sleep CPAP was decreased to 1 cmH(2)O to induce obstructive events and the dial-downs were maintained until the airway opened with or without arousal. GG activity at the instant of opening (GG Opening Threshold) was measured. GG Opening Threshold averaged only 10.4 ± 9.5% GG(Max) and did not correlate with P(CRIT) (r = 0.04). Twenty-six patients had >3 openings without arousal, indicating that Non-Arousal Activation can exceed GG Opening Threshold in the majority of patients. GG activity reached before arousal in Arousal-Associated Openings was only 5.4 ± 4.6% GG(MAX) below GG Opening Threshold. We conclude that in most patients GG activity required to open the airway is modest and can be reached by non-arousal mechanisms. Arousals occur in most cases just before non-arousal mechanisms manage to increase activity above GG Opening Threshold. Measures to reduce GG Opening Threshold even slightly may help stabilize breathing in many patients.
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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".