Mechanisms of exertional dyspnea in patients with cancer
Bibliographic record
Abstract
Exertional dyspnea is an important symptom in cancer patients, and, in many cases, its cause remains unexplained after careful clinical assessment. To determine mechanisms of exertional dyspnea in a variety of cancer types, we evaluated cancer outpatients with clinically important unexplained dyspnea (CD) at rest and during exercise and compared the results with age-, sex-, and cancer stage-matched control cancer (CC) patients and age- and sex-matched healthy control participants (HC). Participants (n = 20/group) were screened to exclude clinical cardiopulmonary disease and then completed dyspnea questionnaires, anthropometric measurements, muscle strength testing, pulmonary function testing, and incremental cardiopulmonary treadmill exercise testing. Dyspnea intensity was greater in the CD group at peak exercise and for a given ventilation and oxygen uptake (P < 0.05). Peak oxygen uptake was reduced in CD compared with HC (P < 0.05), and breathing pattern was more rapid and shallow in CD than in the other groups (P < 0.05). Reduced tidal volume expansion during exercise correlated with reduced inspiratory capacity, which, in turn, correlated with reduced inspiratory muscle strength. Patients with cancer had a relatively reduced diffusing capacity of the lung for carbon monoxide, reduced skeletal muscle strength, and lower ventilatory thresholds during exercise compared with HC (P < 0.05). There were no significant between-group differences in measurements of airway function, pulmonary gas exchange, or cardiovascular function during exercise. In the absence of evidence of airway obstruction or restrictive interstitial lung disease, the shallow breathing pattern suggests ventilatory muscle weakness as one possible explanation for increased dyspnea intensity at a given ventilation in CD patients.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".