Anti-Inflammatory and Anti-Catabolic Effects of Creatine Supplementation: A Brief Review
Bibliographic record
Abstract
It is well established that creatine supplementation, primarily when combined with resistance training, significantly increases measures of muscle mass and performance (primarily strength). Emerging research also indicates that creatine supplementation may have favorable effects on measures of bone biology. These anabolic adaptations may be related to creatine influencing cellular hydration status, high-energy phosphate metabolism, growth factors, muscle protein kinetics, and the bone remodeling process. Accumulating research also suggests that creatine supplementation has anti-inflammatory and anti-catabolic properties, which may help create a favorable environment for muscle and bone accretion and recovery from exercise. Creatine supplementation has the ability to decrease markers of inflammation and possibly attenuate cancerous tumor growth progression. From a musculoskeletal perspective, there is some evidence to show that creatine supplementation reduces measures of muscle protein catabolism (primarily in males) and bone resorption when combined with resistance training. The purpose of this brief review is to summarize the current body of literature examining the potential anti-inflammatory and anti-catabolic effects of creatine supplementation across various research populations.
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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 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".