Effects of creatine supplementation on memory in healthy individuals: a systematic review and meta-analysis of randomized controlled trials
Bibliographic record
Abstract
CONTEXT: From an energy perspective, the brain is very metabolically demanding. It is well documented that creatine plays a key role in brain bioenergetics. There is some evidence that creatine supplementation can augment brain creatine stores, which could increase memory. OBJECTIVE: A systematic review and meta-analysis of randomized controlled trials (RCTs) was conducted to determine the effects of creatine supplementation on memory performance in healthy humans. DATA SOURCES: The literature was searched through the PubMed, Web of Science, Cochrane Library, and Scopus databases from inception until September 2021. DATA EXTRACTION: Twenty-three eligible RCTs were initially identified. Ten RCTs examining the effect of creatine supplementation compared with placebo on measures of memory in healthy individuals met the inclusion criteria for systematic review, 8 of which were included in the meta-analysis. DATA ANALYSIS: Overall, creatine supplementation improved measures of memory compared with placebo (standard mean difference [SMD] = 0.29, 95%CI, 0.04-0.53; I2 = 66%; P = 0.02). Subgroup analyses revealed a significant improvement in memory in older adults (66-76 years) (SMD = 0.88; 95%CI, 0.22-1.55; I2 = 83%; P = 0.009) compared with their younger counterparts (11-31 years) (SMD = 0.03; 95%CI, -0.14 to 0.20; I2 = 0%; P = 0.72). Creatine dose (≈ 2.2-20 g/d), duration of intervention (5 days to 24 weeks), sex, or geographical origin did not influence the findings. CONCLUSION: Creatine supplementation enhanced measures of memory performance in healthy individuals, especially in older adults (66-76 years). SYSTEMATIC REVIEW REGISTRATION: PROSPERO registration no. 42021281027.
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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 | 0.015 | 0.044 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.035 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".