High-intensity interval training with blood-flow restriction enhances sprint and maximal aerobic power in male endurance athletes
Bibliographic record
Abstract
High-intensity interval training (HIIT) can improve endurance performance. We investigated the concurrent impact of HIIT and blood-flow restriction (BFR) as a novel approach to further enhance maximal aerobic and anaerobic physiology and performances in trained athletes. In a randomized controlled trial, eighteen endurance-trained males ([Formula: see text]O2peak 65.6 ± 5.1 mL.min−1.kg−1) included three sessions of HIIT per week (sets of 15 s efforts at 100% maximal aerobic power, interspersed by 15 s recovery) into their usual training for 3 weeks, either with restriction imposed on both lower limbs at 50%–70% of arterial occlusion pressure (BFR group, n = 10) or without (CTL group, n = 8), and were tested for sprint and endurance exercise performance. The total mechanical work developed during a 30 s Wingate test increased only in BFR (3.6%, P = 0.02). During the Wingate, changes in near-infrared spectroscopy-derived vastus lateralis muscle oxygenation (Δ(deoxy[Hb + Mb]), % arterial occlusion) were attenuated after BFR training (−8.8%, P = 0.04). The maximal aerobic power measured during an incremental cycling test increased only in BFR (4.5%, P = 0.0004), but there was no change in [Formula: see text]O2peak among groups. Both groups improved 5 km cycling time trial performance, but BFR displayed a concomitant greater elevation in [H+] (11%, P = 0.02). Changes in other blood variables (e.g., pH, lactate, bicarbonate and potassium ion concentration, and hemoglobin) were not different between groups. Combining short-duration HIIT performed at 100% aerobic power with BFR elicited greater changes in sprint performance and maximal aerobic power in endurance athletes, associated with locomotor muscle metabolic adaptations but no meaningful effect on cardiorespiratory fitness.
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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) | 0.001 | 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 | 0.001 |
| 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".