Reversibility of Airflow Obstruction by Hypoglossus Nerve Stimulation in Anesthetized Rabbits
Bibliographic record
Abstract
RATIONALE: Anesthesia-induced uncoupling of upper airway dilating and inspiratory pump muscles activation may cause inspiratory flow limitation, thereby mimicking obstructive sleep apnea/hypopnea. OBJECTIVES: Determine whether inspiratory flow limitation occurs in spontaneously breathing anesthetized rabbits and whether this can be reversed by direct hypoglossal nerve stimulation and by the application of continuous positive airway pressure. METHODS: Ten New Zealand White rabbits were anesthetized, instrumented, and studied supine while breathing spontaneously at ambient pressure or during the application of positive or negative airway pressure. Under each of these conditions, the effect of unilateral or bilateral hypoglossal nerve stimulation was investigated. MEASUREMENTS: Inspiratory flow and tidal volume were measured together with esophageal pressure and the electromyographic activity of diaphragm, alae nasi, and genioglossus muscles. MAIN RESULTS: Anesthesia caused a marked increase in inspiratory resistance, snoring, and in eight rabbits, inspiratory flow limitation. Hypoglossus nerve stimulation was as effective as continuous positive airway pressure in reversing inspiratory flow limitation and snoring. Its effectiveness increased progressively as airway opening pressure was lowered, reached a maximum at -5 cm H2O, but declined markedly at lower pressures. With negative airway opening pressure, airway collapse eventually occurred during inspiration that could be prevented by hypoglossus nerve stimulation. The recruitment characteristics of hypoglossus nerve fibers was steep, and significant upper airway dilating effects already obtained with stimulus intensities 36 to 60% of maximum. CONCLUSION: This study supports hypoglossus nerve stimulation as a treatment option for obstructive sleep apnea.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".