The Effects of Creatine Supplementation on Markers of Muscle Damage and Inflammation Following Exercise in Older Adults: A Brief Narrative Review
Bibliographic record
Abstract
Exercise induced muscle damage occurs following strenuous and unfamiliar exercise and results in biomarkers of muscle damage and inflammation in the circulation. Creatine (Cr) is a commonly utilized nutritional supplement which has been proposed to enhance post-exercise recovery and has been suggested to decrease exercise induced inflammation. Exercise is well recognized to be beneficial for older adults to maintain skeletal muscle mass and strength as well as promote health for other biological systems. However, older adults can experience chronic low-grade inflammation, sometimes referred to as ‘inflammaging’. Therefore, it may be prudent to limit post-exercise induced skeletal muscle damage and inflammation for the older adult population who may already be in a pro-inflammatory state and at risk of age-related muscle loss (sarcopenia). The purpose of this brief narrative review is to outline the current research on Cr and its effects on biomarkers of muscle damage and inflammation in older adults. Further, the review will suggest areas of research that are required to fully understand how Cr supplementation may affect muscle damage and inflammatory biomarkers in older adults who exercise.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".