Eccentric cycling exercise: A novel form of rehabilitation for patients with severe COPD?
Bibliographic record
Abstract
During eccentric muscle contractions, greater levels of force are generated with lower metabolic cost, which can be an attractive alternate rehabilitation for severe COPD. The aim of this study is to estimate the extent to which eccentric compared to concentric training produces greater increases in isometric muscle force and fat free mass in patients with severe COPD. For this, a pilot randomized control trial was conducted in which 20 patients with COPD were randomly assigned to either high intensity concentric (CON, n=10) or eccentric (ECC, n=10) cycling training. Patients exercised 3 times per week, during 30 minutes and for the period of 10 weeks. Musle biopsy was conducted in a subgroup of 12 patients (CON, n=06, ECC, n=06). Study participants were older subjects (age: 65 (5) years old) with severe COPD (FEV%pred: 40 (9) %predicted) and with significant muscle weakness (quadriceps force:103(10)NM). Significant increases in isometric quadriceps force were found in the ECC group (+18Nm, 17% increase from baseline; p <0.05), but not in the concentric (+9Nm, 5% increase from baseline; p >0.05). Fat-free mass index (kg/m2) increased post-training (17.4±1.7kg/m2 to 17.6±1.7kg/m2) in the ECC group and decreased (18.5±2.7kg/m2 to 18.2±2.8kg/m2) in the CON group (p<0.05). ECC cycling may be a valuable training modality for patients with advanced COPD due to its moderately greater augmenting effect on muscle strength and fat free mass than CON cycling, which may prove its relevance in preventing disease related muscle atrophy in patients with COPD. However, the clinical significant of these improvements remains to be shown.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".