Contemporary issues in refractory dyspnoea in advanced chronic obstructive pulmonary disease
Bibliographic record
Abstract
PURPOSE OF REVIEW: Relieving dyspnoea when chronic obstructive pulmonary disease (COPD) no longer responds to disease-modifying therapy is challenging, with limited evidence to provide guidance. This review highlights recent advances that further our understanding and management of refractory dyspnoea in COPD, focusing on interventions that are considered beyond the conventional treatment of airflow obstruction/hyperinflation. RECENT FINDINGS: Advances in functional brain imaging have improved our understanding of limbic system activation in dyspnoea, providing insight into potential for targeted treatments. Qualitative research is defining the complexities of the multidimensional aspects of dyspnoea, supporting the need to address dyspnoea-related affective distress in prospective outcomes-based research. Studies evaluating inhaled furosemide in exertional dyspnoea and palliative noninvasive ventilation in advanced disease support ongoing work in this area. In addition, recent advances in delivery of rapidly acting opioids offer intriguing potential for management of incidental dyspnoea in advanced disease. SUMMARY: Improved understanding of the nature of dyspnoea in advanced COPD, advances in symptom mapping and noninvasive ventilatory support along with the potential of novel treatments offer hope that we can improve the management of refractory dyspnoea in COPD. Where evidence is lacking, we outline options that merit further evaluation.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".