Exercise training improves exercise capacity and quality of life in people with interstitial lung disease [synopsis]
Bibliographic record
Abstract
Question: Does exercise training improve functional exercise capacity, muscle strength, health-related quality of life, dyspnoea, anxiety and depression in people with interstitial lung disease?Design: Randomised, controlled trial with concealed allocation and blinded outcome assessment.Setting: Three tertiary hospitals in Melbourne, Australia.Participants: People with interstitial lung disease were eligible for inclusion if they were clinically stable, ambulant, and reported dyspnoea on exertion despite maximal medical treatment.Exclusion criteria were respiratory disease other than interstitial lung disease, history of syncope on exertion, and co-morbidity that prevented exercise.Randomisation of 142 participants allocated 68 to a control group and 74 to an intervention group.Interventions: Both groups received usual medical care.The intervention group participated in an 8-week supervised outpatient exercise-training program consisting of 30 minutes of aerobic exercise (cycling and walking), and upper and lower limb resistance training.Outcome measures: The primary outcome was the change in 6-minute walking distance at the 9-week and 6-month follow-up.Secondary outcome measures comprised knee and elbow flexor strength, quality of life, dyspnoea, and feelings of anxiety and depression.Results: A total of 126 participants completed the study.At the 9-week follow-up, the change in
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.025 | 0.025 |
| Insufficient payload (model declined to judge) | 0.004 | 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".