Variable effects of respiratory muscle training on cycle exercise performance in men and women
Bibliographic record
Abstract
Respiratory muscle training (RMT) has been proposed as an effective means to increase the strength of the inspiratory muscles and improve exercise performance. The purpose of this study was to examine the effect of RMT on cycling time to exhaustion (TTE) and to determine any potential sex effect. We hypothesized that RMT would improve maximal inspiratory pressure (MIP) and TTE to a similar degree in men and women. Males (n = 7; mean (+/- SD) age, 22.1 +/- 1.5 y) and females (n = 8; mean (+/- SD) 24.5 +/- 4.9 y) performed an incremental cycle test to determine maximal oxygen consumption ((.)VO(2) (max)) (day 1), followed by a familiarization TTE (day 2) and baseline TTE (day 3) at 80% maximal work achieved during the ((.)VO(2) (max)) test. Subjects then completed 5 weeks of respiratory muscle training (RMT) (5 d/week, 2 sets of 30 inspirations against 50% MIP). Four training sessions per week were performed at home and the 5th was supervised, during which the threshold load was increased if necessary. Following RMT, subjects completed 2 TTE tests (days 4 and 5). MIP increased in each subject (37% +/- 18%, P < 0.05). There was no difference between men (pre = -100 +/- 20 vs. post = -140 +/- 29 cmH(2)O) and women (pre = -90 +/- 28 vs. post = -117 +/- 28 cmH(2)O). Baseline TTE (male = 301 +/- 122 s; female = 338 +/- 98 s) was shorter in comparison with the best of the 2 TTE-post tests (male = 353 +/- 68 s; female = 416 +/- 116 s; P < 0.01), but not when compared with days 4 or 5 (P > 0.05). RMT increases MIP and may improve exercise performance; however, improvements are variable with no differences between men and women.
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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 | 0.002 |
| 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 | 0.000 | 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".