Dyspnoea: a multidimensional and multidisciplinary approach
Bibliographic record
Abstract
Dyspnoea is a debilitating symptom that affects quality of life, exercise tolerance and mortality in various disease conditions/states. In patients with chronic obstructive pulmonary disease (COPD), it has been shown to be a better predictor of mortality than forced expiratory volume in 1 s. In patients with heart disease it is a better predictor of mortality than angina. Dyspnoea is also associated with decreased functional status and worse psychological health in older individuals living at home. It also contributes to the low adherence to exercise training programmes in sedentary adults and in COPD patients. The mechanisms of dyspnoea are still unclear. Recent studies have emphasised the multidimensional nature of dyspnoea in the sensory-perceptual (intensity and quality), affective distress and impact domains. The perception of dyspnoea involves a complex chain of events that depend on varying cortical integration of several afferent/efferent signals and coloured by affective processing. This review, which stems from the European Respiratory Society research symposium held in Paris, France in November 2012, aims to provide state-of-the-art advances on the multidimensional and multidisciplinary aspects of dyspnoea, by addressing three different themes: 1) the neurophysiology of dyspnoea, 2) exercise and dyspnoea, and 3) the clinical impact and management of dyspnoea.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| 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".