The Effect Of Blood-Flow Restriction On Muscle Function During A Single Bout Of Explosive Training
Bibliographic record
Abstract
Intro: There is evidence to support the use of blood-flow restriction (BFR) in combination with resistance training to promote a positive change in muscle strength and power among healthy individuals. However, no study has yet to report the effect of BFR-induced fatigue on muscle function during short bouts of explosive effort. PURPOSE: To compare muscle function during a single bout of explosive training under two different conditions: with BFR and without BFR (control). METHODS: 15 participants (age 25.33 ± 3.08, height 175.36 ± 8.19 cm, body mass 79.90 ± 10.26 kg) performed a 30-second consecutive countermovement jump test under two different conditions in randomized order. Under the BFR condition, cuff pressure was set to 80% arterial occlusion pressure of the lower limb at rest (Delfi Medical, Vancouver, Canada). Participants performed a series of repeated countermovement jumps (CMJ) for 30 seconds on force plates sampling at 1000 Hz (VALD Performance, Newstead, Australia). Muscle performance was assessed by measuring jumping height. RESULTS: Statistical analyses were performed using a two-tailed paired t-test to assess differences between jump height at different time intervals: 0-5 seconds (t1,), 15-20 seconds (t2), and 25-30 seconds (t3). Alpha level was set at p = 0.05. For each time interval, the average jump height was calculated. At baseline (t1), no significant difference emerged between conditions (6.4%; p = 0.094; p < 0.05). No significant difference in the overall decline in muscle function was measured between conditions at t2 (p = 0.385; p < 0.05) and t3 (p = 0.103; p < 0.05). CONCLUSIONS: When compared to the control group, the use of BFR did not result in a more appreciable decline in muscle function during a single bout of explosive training lasting 30 seconds or less. These findings suggest no apparent negative effect of BFR on muscle function during short bouts of anaerobic 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 | 0.001 | 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) | 0.002 | 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".