Breathlessness abnormality is best assessed at peak exercise during incremental cardiopulmonary cycle exercise testing
Bibliographic record
Abstract
Background: Breathlessness on exertion is the cardinal symptom in cardiorespiratory disease and can be quantified on incremental cardiopulmonary exercise testing (CPET) using normative reference equations. We evaluated the hypothesis that breathlessness abnormality would be uncovered and best assessed at symptom limitation (peak exercise) compared with using submaximal ratings. Methods: Analysis of people aged ≥40 years undergoing symptom-limited incremental cycle CPET in the CanCOLD study. Each breathlessness Borg 0-10 rating during CPET was converted to its probability of being normal (Pnorm), in relation to W, V’O2 and V’E using normative reference equations. Abnormal breathlessness was defined as a Pnorm<0.05. Results: Of 1,161 participants (42% women), abnormal breathlessness was present in 22%, 23% and 16% in relation to W, V’O2 and V’E at peak exercise. Among those with abnormal breathlessness at peak exercise, 55-60% had normal breathlessness across all sub-peak ratings. Among those with normal peak breathlessness, 93-97% were normal across all breathlessness ratings throughout the CPET, ICC 0.93-0.95. Findings were similar in people without or with chronic airflow limitation, and in people with non-maximal tests. Conclusion: Abnormal breathlessness is uncovered and should be assessed at peak exercise during symptom-limited incremental CPET. These findings inform symptom assessment in research and clinical practice.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".