Multi-ingredient pre-workout supplementation changes energy system contribution and improves performance during high-intensity intermittent exercise in physically active individuals: a double-blind and placebo controlled study
Bibliographic record
Abstract
Background Nutritional ergogenic aids are commonly used to boost physiological adaptations to exercise and promote greater fitness gains. However, there is a paucity of data about multi-ingredient pre-workout supplementation (MIPS). Therefore, the aim of the present study was to investigate the acute effects of MIPS on the oxidative, glycolytic and ATP-CP energy systems contribution, time spent above 90% V̇O2max (T90% V̇O2max), excess post-exercise oxygen consumption (EPOC) magnitude, number of efforts and time to exhaustion during a high-intensity interval exercise (HIIE) session.Methods Twelve physically-active and healthy men completed the HIIE sessions that involved running bouts of 15 s on the treadmill at 120% of the maximum aerobic speed (MAS), interspersed with 15 s of passive recovery. Blood lactate was collected at immediately post, 3, 5, and 7 min post exercise. The contribution of ATP-CP, glycolytic and oxidative systems was analyzed at rest, during the HIIE sessions and for 20 min post. Performance variables (time to exhaustion, number of efforts) and oxygen consumption were also analyzed.Results MIPS significantly increased the number of efforts performed (MIPS: 41 ± 10 vs Placebo: 36 ± 12, p = 0.0220) and time to exhaustion (MIPS: 20.1 ± 6 min vs Placebo: 17 ± 5 min, p = 0.0226). There was no difference between supplements for both T90% V̇O2max (p = 0.9705) and EPOC (p = 0.4930). Consuming MIPS significantly increased the absolute oxidative energy system contribution by 23.8% (p = 0.0163) and the absolute ATP-CP contribution by 28.4% (p = 0.0055) compared to placebo. There was only a non-significant tendency for a higher glycolytic system contribution after MIPS ingestion (p = 0.0683).Conclusion Acute MIPS ingestion appears effective at increasing both aerobic and anaerobic alactic energy contribution and time to exhaustion during a HIIE protocol.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".