Low-Dose Creatine Combined with Protein during Resistance Training in Older Men
Bibliographic record
Abstract
PURPOSE: To determine whether low-dose creatine and protein supplementation during resistance training (RT; 3 d x wk(-1); 10 wk) in older men (59-77 yr) is effective for improving strength and muscle mass without producing potentially cytotoxic metabolites (formaldehyde). METHODS: Older men were randomized (double-blind) to receive 0.1 g x kg(-1) creatine + 0.3 g x kg(-1) protein (CP; n = 10), creatine (C; n = 13), or placebo (PLA; n = 12) on training days. Measurements before and after RT included lean tissue mass (air-displacement plethysmography), muscle thickness (ultrasound) of elbow, knee, and ankle flexors and extensors, leg and bench press strength, and urinary indicators of cytotoxicity (formaldehyde), myofibrillar protein degradation [3-methylhistidine (3-MH)],and bone resorption [cross-linked N-telopeptides of type I collagen (NTx)]. RESULTS: Subjects in C and CP groups combined experienced greater increases in body mass and total muscle thickness than PLA (P < 0.05). Subjects who received CP increased lean tissue mass (+5.6%) more than C (+2.2%) or PLA (+1.0%; P < 0.05) and increased bench press strength (+25%) to a greater extent than C and PLA combined (+12.5%; P < 0.05). CP and C did not differ from PLA for changes in formaldehyde production (+24% each). Subjects receiving creatine (C and CP) experienced a decrease in 3-MH by 40% compared with an increase of 29% for PLA (P < 0.05) and a reduction in NTx (-27%) versus PLA (+13%; P = 0.05). CONCLUSIONS: Low-dose creatine combined with protein supplementation increases lean tissue mass and results in a greater relative increase in bench press but not leg press strength. Low-dose creatine reduces muscle protein degradation and bone resorption without increasing formaldehyde production.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".