Energy economy of walking with a wheeled ambulatory aid (rollator) in patients with chronic obstructive pulmonary disease (COPD)
Bibliographic record
Abstract
Background: Probst et al. (Chest 126: 1102, 2004) reported that, when using a rollator, patients with COPD increased their distance walked in 6 min along with increased oxygen uptake and ventilation. It was difficult to appraise economy (mechanical work to total energy expenditure) because the main determinant of the energy demand, speed, varied between conditions; hence, the authors concluded that rollator use improved distance by increasing ventilatory capacity and/or economy. Objective: To determine whether walking with a rollator improved the energy economy in patients with COPD. The hypothesis was that oxygen uptake, at the same speed, would be lower (improved economy) when walking with a rollator. Methods: Subjects completed 2 walks, (with and without a rollator) at individually set and constant speeds. At least 24 h later they repeated the session for a total of 4 walks. Energy expenditure was estimated from measured oxygen uptake using a telemetric system. Since mechanical work was kept constant (speed) during each walk, differences in economy were reflected in differences in energy expenditure in metabolic equivalents (METS). Results: Ten subjects completed the study. Attainment of a steady state was confirmed during every walk. There was no effect of day (p=0.23) on energy expenditure. There was no significant difference (0.0 [-0.4 to 0.3] METS) in energy expenditure with (3.6 [2.9 to 4.3] METS) or without (3.6 [2.9 to 4.3] METS) the rollator. Conclusion: Rollator use does not acutely affect walking economy in patients with COPD. A better understanding of how people with COPD benefit from rollator use may facilitate their design and prescription.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".