Non-linear periodized resistance training in COPD: an international multicentre RCT
Bibliographic record
Abstract
Introduction: Resistance training (RT) is a key component of pulmonary rehabilitation for people with COPD; however, whether the effects of RT could be optimized by utilizing the exercise principle of non-linear periodization is yet to be determined. Method: An international multicenter RCT was conducted across three countries. Fifty-seven people with COPD (70+7 yrs, FEV1% 49+21, 58% male) were randomized to 8 weeks of RT designed per current COPD guidelines to improve muscle strength or to non-linear periodized resistance training (NLPRT) designed to improve muscle strength [4 weeks] but also muscle endurance [4 weeks]. Outcomes included muscle strength, muscle endurance, functional exercise capacity (1-minute sit-to-stand [1-STS], endurance shuttle walk test [ESWT], Unsupported Upper Limb Exercise test [UULEX]), and disease-specific quality of life (QoL). Intention-to-treat (ITT) analysis was utilized, and Cohen's D Effect Sizes [ES] were calculated. Result: ITT analysis demonstrated that NLPRT resulted in more pronounced effects on muscle strength (+33% vs. +21%, ES 0.928), muscle endurance (+147% vs. +50%, ES 1.080), ESWT (+168m vs. +36m, ES 0.592), 1-STS (+4 STS vs. 1 STS, ES 0.864), UULEX (+142sec vs. + 42sec, ES=0.819) (all p<0.05) when compared to RT. Both NLPRT and RT resulted in clinically relevant improvements in QoL without differences between modalities. Conclusion: These results indicate that 8 weeks of NLPRT yields significantly better outcomes in various dimensions of muscle function and functional capacity when compared to 8 weeks of traditional RT. Consequently, this suggests a potential need for reevaluating and updating current RT guidelines to incorporate these findings.
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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 | 0.022 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".