Acute creatine loading increases fat-free mass, but does not affect blood pressure, plasma creatinine, or CK activity in men and women
Bibliographic record
Abstract
UNLABELLED: Creatine monohydrate (CrM) administration may enhance high intensity exercise performance and increase body mass, yet few studies have examined for potential adverse effects, and no studies have directly considered potential gender differences. PURPOSE: The purpose of this study was to examine the effect of acute creatine supplementation upon total and lean mass and to determine potential side effects in both men and women. METHODS: The effect of acute CrM (20 g x d(-1) x 5 d) administration upon systolic, diastolic, and mean BP, plasma creatinine, plasma CK activity, and body composition was examined in 15 men and 15 women in a randomized, double-blind experiment. Additionally, ischemic isometric handgrip strength was measured before and after CrM or placebo (PL). RESULTS: CrM did not affect blood pressure, plasma creatinine, estimated creatinine clearance, plasma CK activity, or handgrip strength (P > 0.05). In contrast, CrM significantly increased fat-free mass (FFM) and total body mass (P < 0.05) as compared with PL, with no changes in body fat. The observed mass changes were greater for men versus women. CONCLUSIONS: These findings suggest that acute CrM administration does not affect blood pressure, renal function, or plasma CK activity, but increases FFM. The effect of CrM upon FFM may be greater in men as compared with that in women.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".