Mechanisms, measurement and management of exertional dyspnoea in asthma
Bibliographic record
Abstract
Asthma is a heterogeneous condition, with dyspnoea during exercise affecting individuals to a variable degree. This narrative review explores the mechanisms and measurement of exertional dyspnoea in asthma and summarises the available evidence for the efficacy of various interventions on exertional dyspnoea. Studies on the mechanisms of dyspnoea in asthma have largely utilised direct bronchoprovocation challenges, rather than exercise, which may invoke different physiological mechanisms. Thus, the description of dyspnoea during methacholine challenge can differ from what is experienced during daily activities, including exercise. Dyspnoea perception during exercise is influenced by many interacting variables, such as asthma severity and phenotype, bronchoconstriction, dynamic hyperinflation, respiratory drive and psychological factors. In addition to the intensity of dyspnoea, the qualitative description of dyspnoea may give important clues as to the underlying mechanism and may be an important endpoint for future interventional studies. There is currently little evidence demonstrating whether pharmacological or non-pharmacological interventions specifically improve exertional dyspnoea, which is an important area for future research.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| 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".