Effectiveness of Respiratory Muscles Training by Voluntary Isocapnic Hyperpnea Versus Inspiratory Threshold Loading on Intercostales and Vastus Lateralis Muscles Deoxygenation Induced by Exercise in Physically Active Adults
Bibliographic record
Abstract
Respiratory muscle training (RMT) improves physical performance, although it is still debated whether this effect depends on the type of training. The purpose of this study was to compare the effects of two different types of RMT, i.e., voluntary isocapnic hyperpnea (VIH) and inspiratory threshold loading (ITL), on the deoxygenation of intercostal (ΔSmO2-m. intercostales) and vastus lateralis (ΔSmO2-m. vastus lateralis) muscles during exercise. Twenty-four participants performed eight weeks of RMT by: (i) VIH (3 days·week−1 for 12 min at 60% maximal voluntary ventilation) or (ii) ITL (5 sets·week−1 of 30 breaths·minute−1 at 60% maximal inspiratory pressure). Cardiopulmonary exercise testing (CPET) included ΔSmO2 (the change from baseline to end of test) of intercostal and vastus lateralis muscles. After RMT, both groups showed decreased ΔSmO2-m. intercostales (VIH = 12.8 ± 14.6%, p = 0.04 (effect size, ES = 0.59), and ITL = 8.4 ± 9.8%, p = 0.04 (ES = 0.48)), without a coincident change of ∆SmO2-m. vastus lateralis. ITL training induced higher V˙O2-peak absolute values than VIH (mean Δ post–pre, ITL = 229 ± 254 mL·min−1 [95% CI 67–391] vs. VIH, 39 ± 153 mL·min−1 [95% CI −58–136.0], p = 0.01). In conclusion, both RMT improved the balance between supply and oxygen consumption levels of m. intercostales during CPET, with ITL also inducing an increase of aerobic capacity.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.001 | 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".