Breathlessness dimensions should be evaluated in relation to the level of exertion: A clinical study
Bibliographic record
Abstract
BACKGROUND/AIM: Exertional breathlessness is a dominating symptom in cardiorespiratory disease, limiting exercise capacity. Multidimensional measurement has been proposed to capture breathlessness, but it is unknown whether it is useful to differentiate people with abnormal vs normal exertional breathlessness intensity. METHODS: This was a secondary analysis of a randomized controlled trial of outpatients aged ≥ 18 years performing a symptom-limited cycle incremental exercise test (IET). Breathlessness sensations at end of IET were identified using the multidimensional dyspnea profile (MDP) 30-min post-exercise and compared between people with abnormally high breathlessness (Borg 0-10 rating > upper limit of normal [ULN]) and people within normal ranges (≤ ULN) in relation to the percentage of predicted peak power output defined by normative reference equations. RESULTS: Of 92 participants, 20 (22 %) had abnormally high breathlessness. Compared with those with normal breathlessness (n = 72 [78 %]), the abnormal group reported higher symptom intensity at peak exercise (7.9 ± 1.7 vs 6.3 ± 1.4 Borg units; p < 0.001) and had lower peak power output 129 ± 52 W vs 167 ± 55 W; p < 0.001). Differences between those with normal, and abnormal exertional breathlessness regarding MDP ratings were not statistically significant (all p > 0.05): overall unpleasantness, 4.1 ± 2.3 vs 4.7 ± 1.6; immediate perception, 10.9 ± 2.8 vs 11.5 ± 1.8; and emotional response, 4.1 ± 7.6 vs 3.2 ± 7.5. MDP ratings had no relation to peak power output. CONCLUSION: Breathlessness dimensions are similar at the peak of a standardized IET and cannot differentiate between people with normal and abnormally high exertional breathlessness.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".