Mechanical Properties of the Lung and Upper Airways in Patients with Sleep-disordered Breathing
Bibliographic record
Abstract
We studied the changes in lung and upper airway mechanics in adult human subjects with obstructive sleep apnea/hypopnea syndrome (OSAHS) during wakefulness, sleep, and at arousal from sleep. We used two numerical methods that we have previously developed specifically for dealing with inspiratory flow limitation during sleep: the modified Mead-Whittenberger method, and information-weighted histograms obtained using recursive least squares. Full polysomnography including esophageal pressure and airflow measurements was performed in seven men with OSAHS (respiratory disturbance index: 55.8 +/- 23.2 events/h). Pharyngeal pressure was recorded in four of the subjects to partition lung mechanics into its upper airway and lower lung components. Both techniques showed that total lung resistance and elastance increased significantly (p < 0.05) during obstructed breathing and that this increase was reversed at the end of the obstruction. The partitioning of mechanics showed that upper airway collapse was primarily responsible for the increase in lung resistance. Our results suggest that OSAHS may lead to transient abnormalities in the recruitment of lung units and the gas exchanging capacity of the lungs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".