Efficacy of Creatine Supplementation and Resistance Training on Area and Density of Bone and Muscle in Older Adults
Bibliographic record
Abstract
PURPOSE: To examine the efficacy of creatine (Cr) supplementation and any sex differences during supervised whole-body resistance training (RT) on properties of bone and muscle in older adults. METHODS: Seventy participants (39 men, 31 women; mean age ± standard deviation: 58 ± 6 yr) were randomized to supplement with Cr (0.1 g·kg-1·d-1) or placebo (Pl) during RT (3 d·wk-1 for 1 yr). Bone geometry (radius and tibia) and muscle area and density (forearm and lower leg) were assessed using peripheral quantitative computed tomography. RESULTS: Compared with Pl, Cr increased or maintained total bone area in the distal tibia (Cr, Δ +17 ± 27 mm2; Pl, Δ -1 ± 22 mm2; P = 0.031) and tibial shaft (Cr, Δ 0 ± 9 mm2; Pl, Δ -5 ± 7 mm2; P = 0.032). Men on Cr increased trabecular (Δ +28 ± 31 mm2; P < 0.001) and cortical bone areas in the tibia (Δ +4 ± 4 mm2; P < 0.05), whereas men on Pl increased trabecular bone density (Δ +2 ± 2 mg·cm-3; P < 0.01). There were no bone changes in the radius (P > 0.05). Cr increased lower leg muscle density (Δ +0.83 ± 1.15 mg·cm-3; P = 0.016) compared with Pl (Δ -0.16 ± 1.56 mg·cm-3), with no changes in the forearm muscle. CONCLUSIONS: One year of Cr supplementation and RT had some favorable effects on measures of bone area and muscle density in older adults.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".