Dietary Creatine Supplementation and Exercise Performance: Why Inconsistent Results?
Bibliographic record
Abstract
Over the past few years there has been considerable interest in both the use of creatine (Cr) supplementation by athletes and the documentation of its effects by scientists. Some believe that this nitrogen-containing compound found in meat and fish has a performance-enhancing capability as important for brief intense exercise efforts as dietary carbohydrate is for activities where glycogen supplies limit performance. The mechanisms thought to be responsible for any ergogenic effect of acute (few d) Cr supplementation include: increased stores of muscle phosphocreatine (PCr), faster regeneration of PCr during exercise recovery, enhanced adenosine triphosphate (ATP) production from glycolysis secondary to increased hydrogen ion buffering, and/or possible shortened post contraction muscle relaxation time. With chronic (wk mo) supplementation when combined with strength training, Cr may alter muscle protein metabolism directly (via decreasing protein breakdown or increasing synthesis) and/or indirectly as a result of a greater training load made possible by its acute ergogenic effects on strength and power. Cr supplementation is not banned by the International Olympic Committee and, with the exception of a small increase in body mass (approximately 1 kg) over the initial 36 d, does not appear to have any adverse side effects, at least with short-term use. Few scientific data are available for more prolonged use (mo or y) but considering the large numbers of athletes using Cr over the past 6+ y and the absence of reported problems, it may be that the often discussed somewhat nebulous long term adverse effects are presently being overestimated. Intakes of 285-300 mg Cr/kg body mass 1 over 36 d or 3050 mg/kg body mass 1 over approximately 4 wk are sufficient to produce benefits (muscle mass and high intensity power gains); however, not all study results are consistent. The focus of this review is to outline some possible explanations for the inconsistent observations reported in the literature. Clearly, if proven to be consistent the benefits of Cr supplementation could extend far beyond the athletic arena to include individuals who experience muscle weakness for a variety of other reasons (e.g., age/disuse, muscle disease, exposure to microgravity, etc).
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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 | 0.031 | 0.086 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".