Activity-related dyspnea in chronic obstructive pulmonary disease: physical and psychological consequences, unmet needs, and future directions
Bibliographic record
Abstract
Nicola A Hanania,1 Denis E O’Donnell21Department of Medicine, Section of Pulmonary and Critical Care, Baylor College of Medicine, Houston, TX, USA; 2Division of Respirology, Department of Medicine, Queen’s University, Kingston, Ontario, CanadaAbstract: Dyspnea is a distressing, debilitating, and near-ubiquitous symptom affecting patients with COPD. In addition to the functional consequences of dyspnea, which include activity limitation and reduced exercise tolerance, it is important to consider its psychological impact on patients with COPD, such as onset of depression or anxiety. Moreover, the anticipation of dyspnea itself can have a significant effect on patients’ emotions and behavior, with patients frequently self-limiting physical activity to avoid what has become the hallmark symptom of COPD. Dyspnea is, therefore, a key target for COPD treatments. Pharmacologic treatments can optimize respiratory mechanics, provide symptom relief, and reduce patients’ increased inspiratory neural drive to breathe. However, it is important to acknowledge the value of non-pharmacologic interventions, such as pulmonary rehabilitation and patient self-management education, which have proven to be invaluable tools for targeting the affective components of dyspnea. Furthermore, it is important to encourage maintenance of physical activity to optimize long-term patient outcomes. Here, we review the physiological and psychological consequences of activity-related dyspnea in COPD, assess the efficacy of modern management strategies in improving this common respiratory symptom, and discuss key unmet clinical and research needs that warrant further immediate attention.Keywords: dyspnea, chronic obstructive pulmonary disease, psychology, physiology, management
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".