A frame of reference for assessing the intensity of exertional dyspnoea during incremental cycle ergometry
Bibliographic record
Abstract
Assessment of dyspnoea severity during incremental cardiopulmonary exercise testing (CPET) has long been hampered by the lack of reference ranges as a function of work rate (WR) and ventilation (V′E). This is particularly relevant to cycling, a testing modality which overtaxes the leg muscles leading to a heightened sensation of leg discomfort. Reference ranges based on dyspnoea percentiles (0–10 Borg scale) at standardised work rates andV′Ewere established in 275 apparently healthy subjects aged 20–85 years (131 men). They were compared with values recorded in a randomly selected “validation” sample (n=451; 224 men). Their usefulness in properly uncovering the severity of exertional dyspnoea were tested in 167 subjects under investigation for chronic dyspnoea (“testing sample”) who terminated CPET due to leg discomfort (86 men). Iso-work rate and, to a lesser extent, iso-V′Ereference ranges (5th–25th, 25th–50th, 50–75th and 75th–95th percentiles) increased as a function of age, being systematically higher in women (p<0.01). There were no significant differences in percentiles distribution between “reference” and “validation” samples (p>0.05). Submaximal dyspnoea-work rate scores fell within the 75th–95th or >95th percentiles in 108 out of 118 (91.5%) subjects of the “testing” sample who showed physiological abnormalities known to elicit exertional dyspnoea,i.e.ventilatory inefficiency and/or critical inspiratory constraints. In contrast, dyspnoea scores typically fell in the 5th–50th range in subjects without those abnormalities (p<0.001). This frame of reference might prove useful to uncover the severity of exertional dyspnoea in subjects who otherwise would be labelled as “non-dyspnoeic” while providing mechanistic insights into the genesis of this distressing symptom.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".