Diaphragm shortening and EMG activity during Continuous Positive Airway Pressure
Bibliographic record
Abstract
Background: Continuous positive airway pressure (CPAP) is widely used in sleep disordered breathing. But, physiologic impact on respiratory parameters, diaphragm function and pre-inspiratory resting length (i.e. FRC) is not known. As the predominant muscle of respiration, diaphragm function during CPAP warrants investigation. Methods: Data from N=10 canines, from a database completed in 2009, previously implanted with sonomicrometers and EMG electrodes into costal diaphragm, was analyzed breath by breath. Breathing pattern, and muscle length, shortening and EMG activity per breath, of costal diaphragm were measured, with incremental CPAP levels: 0/0, 4/4, 8/8, and 12/12 cmH2O. Results: Minute ventilation decreased with increasing CPAP, brought about by reduction in respiratory rate (P<0.01) without change in tidal volume and mean inspiratory flow. Costal diaphragm resting length decreased significantly with increasing CPAP (LBL; P<0.05), accompanied by reduction in both shortening and EMG activity of costal diaphragm (SHORT, EMGDIFF; P<0.01) Conclusion: Positive airway pressure causes significant decrease in diaphragm resting length coupled with reduction in diaphragm shortening and EMG activation respiratory drive. Thus, despite a mechanically disadvantaged diaphragm from CPAP induced lung hyperinflation, paradoxical reduction in EMG/ respiratory drive was noted. erj;64/suppl_68/PA4473/F1 F1 F1
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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".