The Effect of Vitamin D Supplementation to Parameter of Sarcopenia in Elderly People: a Systematic Review and Meta-Analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background Vitamin D plays an essential role in promoting skeletal muscle metabolism. Several studies show that vitamin D may help the elderly prevent sarcopenia. Nevertheless, the outcome remains debatable. Our meta-analysis aimed to summarize the effect of vitamin D supplementation on sarcopenia-related parameters. Methods We searched PubMed, Cochrane, Springer, SAGE Journals, and Scopus abstracts on 10th December 2021 for relevant studies. We included articles that studied the effect of vitamin D on muscle mass, muscle strength, and physical performance. The aim was to measure the muscle mass, muscle strength, and physical performance both at baseline and at the end of the intervention. Results A total of 6,628 participants from 35 studies were included. Most of the studies used oral vitamin D, whereas only one study used intramuscular injection. The effect of vitamin D supplementation showed no effect on appendicular skeletal muscle mass (SMD = .05 [95% CI, .33 – .44], p = .79). Regarding muscle strength, vitamin D supplementation did not have a significant effect on muscle strength which is handgrip strength (p = .26). Respecting physical performance, vitamin D supplementation did not affect TUG (Timed Up and Go) (p = .45). Conclusions Vitamin D supplementation had minimal effect on sarcopenia-related parameters. Further research into understanding the role of Vitamin D in preventing the progressivity of sarcopenia still needs to be explored.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it