Does limb partitioning and positioning affect acute cardiorespiratory responses during strength exercises in patients with <scp>COPD</scp>?
Bibliographic record
Abstract
ABSTRACT Background and objective Cardiorespiratory responses and symptoms in response to endurance exercise in patients with COPD vary with the number and position of involved limbs. Responses to such variations have never been quantified for strength exercises. We therefore assessed acute cardiorespiratory responses during brief bouts of weight lifting exercises. Methods We compared double‐ versus single‐limb leg extensions and arm elevations, as well as arm elevation done above or below shoulder level in patients with moderate to severe COPD ( n = 10, 6 males, 66 (8.1 years), forced expiratory volume on 1 s ( FEV 1 ) % predicted = 34% (14%)). Minute ventilation, oxygen uptake, oxygen saturation, heart rate ( HR ), blood pressure ( BP ), rate of perceived exertion ( RPE ) and recovery time were collected during single sets of each exercise (10 repetitions at 80% of one repetition maximum). Results Ventilatory and gas exchange responses were not affected by the number of exercising limbs. Changes in HR , BP and RPE scores during arm elevation above shoulder level were greater after double‐ compared with single‐arm elevation ( P ≤ 0.001) and greater when exercising above compared with below shoulder level ( P ≤ 0.01). Double‐arm elevation above shoulder level required 1.5 min longer HR recovery time ( P ≤ 0.041) compared with other exercises. Conclusion Double‐arm elevation above shoulder level appears to be more challenging than other strength exercise variations. Partitioning exercises and limb position may reduce perceived exertion during training.
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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 | 0.001 |
| 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) | 0.002 | 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".