Exertional dyspnoea in COPD: the clinical utility of cardiopulmonary exercise testing
Bibliographic record
Abstract
Activity-related dyspnoea is often the most distressing symptom experienced by patients with chronic obstructive pulmonary disease (COPD) and can persist despite comprehensive medical management. It is now clear that dyspnoea during physical activity occurs across the spectrum of disease severity, even in those with mild airway obstruction. Our understanding of the nature and source of dyspnoea is incomplete, but current aetiological concepts emphasise the importance of increased central neural drive to breathe in the setting of a reduced ability of the respiratory system to appropriately respond. Since dyspnoea is provoked or aggravated by physical activity, its concurrent measurement during standardised laboratory exercise testing is clearly important. Combining measurement of perceptual and physiological responses during exercise can provide valuable insights into symptom severity and its pathophysiological underpinnings. This review summarises the abnormal physiological responses to exercise in COPD, as these form the basis for modern constructs of the neurobiology of exertional dyspnoea. The main objectives are: 1) to examine the role of cardiopulmonary exercise testing (CPET) in uncovering the physiological mechanisms of exertional dyspnoea in patients with mild-to-moderate COPD; 2) to examine the escalating negative sensory consequences of progressive respiratory impairment with disease advancement; and 3) to build a physiological rationale for individualised treatment optimisation based on CPET.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".