Positive airway pressure devices for the management of breathlessness
Bibliographic record
Abstract
PURPOSE OF REVIEW: Breathlessness is a common symptom in many chronic diseases and may be refractory to pharmacotherapy. In this review, we discuss the pathophysiology of breathlessness and the role of positive airway pressure (PAP) devices to ameliorate it. RECENT FINDINGS: Breathlessness is directly related to neural respiratory drive, which can be modified by addressing the imbalance between respiratory muscle load and capacity. Noninvasive PAP devices have been applied to patients limited by exertional breathless and, as the disease progresses, breathlessness at rest. The application of PAP is focussed on addressing the imbalance in load and capacity, aiming to reduce neural respiratory drive and breathlessness. Indeed, noninvasive bi-level PAP devices have been employed to enhance exercise capacity by enhancing pulmonary mechanics and reduce neural drive in chronic obstructive pulmonary disease (COPD) patients, and reduce breathlessness for patients with progressive neuromuscular disease (NMD) by enhancing respiratory muscle capacity. Novel continuous PAP devices have been used to maintain central airways patency in patients with excessive dynamic airway collapse (EDAC) and target expiratory flow limitation in severe COPD. SUMMARY: PAP devices can reduce exertional and resting breathlessness by reducing the load on the system and enhancing capacity to reduce neural respiratory drive.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".