Neuromuscular Adjustments Following Sprint Training with Ischemic Preconditioning in Endurance Athletes: Preliminary Data
Bibliographic record
Abstract
This preliminary study examined the effect of chronic ischemic preconditioning (IPC) on neuromuscular responses to high-intensity exercise. In a parallel-group design, twelve endurance-trained males (VO2max 60.0 ± 9.1 mL·kg−1·min−1) performed a 30-s Wingate test before, during, and after 4 weeks of sprint-interval training. Training consisted of bi-weekly sessions of 4 to 7 supra-maximal all-out 30-s cycling bouts with 4.5 min of recovery, preceded by either IPC (3 × 5-min of compression at 220 mmHg/5-min reperfusion, IPC, n = 6) or placebo compressions (20 mmHg, PLA, n = 6). Mechanical indices and the root mean square and mean power frequency of the electromyographic signal from three lower-limb muscles were continuously measured during the Wingate tests. Data were averaged over six 5-s intervals and analyzed with Cohen’s effect sizes. Changes in peak power output were not different between groups. However, from mid- to post-training, IPC improved power output more than PLA in the 20 to 25-s interval (7.6 ± 10.0%, ES 0.51) and the 25 to 30-s interval (8.8 ± 11.2%, ES 0.58), as well as the fatigue index (10.0 ± 2.3%, ES 0.46). Concomitantly to this performance difference, IPC attenuated the decline in frequency spectrum throughout the Wingate (mean difference: 14.8%, ES range: 0.88–1.80). There was no difference in root mean square amplitude between groups. These preliminary results suggest that using IPC before sprint training may enhance performance during a 30-s Wingate test, and such gains occurred in the last 2 weeks of the intervention. This improvement may be due, in part, to neuromuscular adjustments induced by the chronic use of IPC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".