The effect of inspiratory muscle training on high-intensity, intermittent running performance to exhaustion
Bibliographic record
Abstract
The effects of inspiratory muscle (IM) training on maximal 20 m shuttle run performance (Ex) during Yo-Yo intermittent recovery test and on the physiological and perceptual responses to the running test were examined. Thirty men were randomly allocated to 1 of 3 groups. The experimental group underwent a 6 week pressure threshold IM training program by performing 30 inspiratory efforts twice daily, 6 d/week, against a load equivalent to 50% maximal static inspiratory pressure. The placebo group performed the same training procedure but with a minimal inspiratory load. The control group received no training. In post-intervention assessments, IM function was enhanced by >30% in the experimental group. The Ex was improved by 16.3% +/- 3.9%, while the rate of increase in intensity of breathlessness (RPB/4i) was reduced by 11.0% +/- 6.2%. Further, the whole-body metabolic stress reflected by the accumulations of plasma ammonia, uric acid, and blood lactate during the Yo-Yo test at the same absolute intensity was attenuated. For the control and placebo groups, no significant change in these variables was observed. In comparison with previous observations that the reduced RPB/4i resulting from IM warm-up was the major reason for improved Ex, the reduced RPB/4i resulting from the IM training program was lower despite the greater enhancement of IM function, whereas improvement in Ex was similar. Such findings suggest that although both IM training and warm-up improve the tolerance of intense intermittent exercise, the underlying mechanisms may be different.
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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) | 0.001 | 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 | 0.000 | 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".