Effects of hyperoxia on dyspnoea and exercise endurance in fibrotic interstitial lung disease
Bibliographic record
Abstract
Dyspnoea is a major source of distress and is the hallmark symptom of patients with interstitial lung disease (ILD). Supplemental oxygen may alleviate dyspnoea by attenuating arterial oxygen desaturation, increasing oxygen delivery and reducing the drive to breathe; however, previous studies show conflicting results on the effectiveness of supplemental oxygen on dyspnoea and exercise performance in ILD [1–6]. Methodological factors in these studies likely led to underestimation of the potential magnitude of improvement, including an insufficient fraction of inspired oxygen ( F IO2) and/or the use of self-paced walking tests and incremental cycle tests rather than constant-load exercise protocols [3–8]. Dyspnoea was also either not evaluated or only evaluated at peak exercise [1, 3–6], which is insensitive to change compared to more clinically relevant submaximal exercise [8]. Finally, some studies were retrospective and did not include a blinded room-air exercise trial, making it difficult to rule out the potential placebo effect [4, 5]. The purpose of this study was to determine the effects of hyperoxia on exercise endurance as well as the intensity and qualitative dimensions of exertional dyspnoea in patients with fibrotic ILD. Hyperoxia significantly improves exertional dyspnoea and exercise tolerance in patients with fibrotic ILD Author contributions: All authors played a role in the content and writing of the manuscript. J.A. Guenette was the principal investigator and contributed the original idea for the study; M.R. Schaeffer, C.J. Ryerson, A.W. Sheel, N. Khalil, P.G. Camp and J.A. Guenette had input into the study design and conduct of the study; M.R. Schaeffer, C.J. Ryerson, A.H. Ramsook, Y. Molgat-Seon, S.S. Wilkie, R.A. Mitchell and S.S. Dhillon collected the data; and M.R. Schaeffer, C.J. Ryerson, A.H. Ramsook, S.S. Dhillon, R.A. Mitchell and J.A. Guenette performed data analysis.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.021 | 0.018 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".