Can a single bout of treadmill walking improve cognition in people with chronic obstructive pulmonary disease: randomised controlled trial?
Bibliographic record
Abstract
Background: Exercise has been shown to improve cognitive function in the healthy older population, however, the effect of a single bout of treadmill exercise on cognitive function in people with COPD is unknown. Objective: The aim was to determine the effect of a single bout of treadmill walking on cognitive function compared to quiet sitting in people with COPD. Methods: A prospective, randomised, controlled trial with concealed allocation. Patients aged ≥40 years with a diagnosis of COPD who were referred to pulmonary rehabilitation were recruited and randomised into an intervention group (IG) of 20 minutes treadmill walking at 80% of average 6-minute walk test speed or a control group (CG) of 20 minutes of quiet sitting. Cognitive function was measured before and after the intervention or control period using the Montreal Cognitive Assessment (MoCA). Results: 21 participants (IG=10; CG=11), mean (SD) age 70 (5) years, were recruited and all completed the study. There was no significant between-group difference in the change in the total MoCA scores (p=0.72). Conclusion: In people with COPD, a single bout of moderate intensity treadmill exercise, similar to an exercise training session in pulmonary rehabilitation, did not improve overall cognitive function compared to quiet sitting.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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 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".