Reference equations for breathlessness during incremental cycle exercise testing
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background Exertional breathlessness is commonly assessed using incremental exercise testing (IET), but reference equations for breathlessness responses are lacking. We aimed to develop reference equations for breathlessness intensity during IET. Methods A retrospective, consecutive cohort study of adults undergoing IET was carried out in Sweden. Exclusion criteria included cardiac or respiratory disease, death or any of the aforementioned diagnoses within 1 year of the IET, morbid obesity, abnormally low exercise capacity, submaximal exertion or an abnormal exercise test. Probabilities for breathlessness intensity ratings (Borg CR10) during IET in relation to power output (%predW max ), age, sex, height and body mass were analysed using marginal ordinal logistic regression. Reference equations for males and females were derived to predict the upper limit of normal (ULN) and the probability of different Borg CR10 intensity ratings. Results 2581 participants (43% female) aged 18–90 years were included. Mean breathlessness intensity was similar between sexes at peak exertion (6.7±1.5 versus 6.4±1.5 Borg CR10 units) and throughout exercise in relation to %predW max . Final reference equations included age, height and %predW max for males, whereas height was not included for females. The models showed a close fit to observed breathlessness intensity ratings across %predW max values. Models using absolute W did not show superior fit. Scripts are provided for calculating the probability for different breathlessness intensity ratings and the ULN by %predW max throughout IET. Conclusion We present the first reference equations for interpreting breathlessness intensity during incremental cycle exercise testing in males and females aged 18–90 years.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it