Exercise Intervention for Anti-Sarcopenia in Community-Dwelling Older People
Bibliographic record
Abstract
Sarcopenia is an age-related health problem in general communities. Effective exercise programs against sarcopenia remain necessary for community-dwelling older people. In order to summarize the available knowledge on this subject, we collected English articles from a MEDLINE/Pubmed database examining the effects of exercise interventions on sarcopenia-related outcome measures in community-dwelling older people. When nine articles, including eight randomized controlled trials, were reviewed, most studies demonstrated significant improvements in some outcome measures. Indeed, a significant improvement in the muscle mass in one study, muscle strength in two studies and physical performance in two studies was reported among five studies using exercise (E) alone. A significant improvement in the muscle mass in two studies, muscle strength in one study and physical performance in two studies was also reported among four studies using exercise plus nutritional supplementation (EN). Notably, the EN studies appeared to have less extensive exercise interventions than the E studies. One EN study further exhibited significant improvements in all outcome measures. Collectively, exercise could be used as anti-sarcopenic strategies and nutritional interventions when combined with exercise might play a compensated or perhaps a comprehensive role among community-dwelling older people. Limited studies exist and more studies are required for the optimum programs in the community settings.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".