PROGRESSION OF RESISTANCE TRAINING VOLUME IN COPD: A SECONDARY ANALYSIS
Bibliographic record
Abstract
Introduction: Resistance training (RT) is crucial in pulmonary rehabilitation to counteract muscle dysfunction in COPD. However, knowledge about how progression of RT volume is associated with changes in muscle function and functional capacity in COPD is limited. Method: This secondary analysis from a multicenter RCT included 57 COPD patients (70±7 yrs, FEV1% 49±21, 58% male) who performed 8 weeks of either RT to improve muscle strength or to non-linear periodized resistance training (NLPRT) focusing on muscle strength and muscle endurance. Assessment of muscle strength, muscle endurance and functional capacity (1–Minute Sit-To-Stand, Endurance Shuttle Walk Test, and Unsupported Upper Limb Exercise Test) were conducted at baseline and after 8 weeks. Progression of training volume (set x reps x load) was calculated as the percentage change from week one to week eight. Results: Significant associations were found between training volume progression and muscle endurance for both RT (r=.48) and NLPRT (r=.64). Significant associations were also identified between progression of training volume and muscle strength for RT (r=.50) and NLPRT (r=.52) (all <0.05). Progression of training volume was not associated with changes in functional capacity. Discussion: The result from this study indicates that the progression of resistance training volume over time is associated with greater effects on muscle endurance and muscle strength in people with COPD. erj;66/suppl_69/PA4892/F1 F1 F1
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".