Physical exercise and sarcopenia in older people: an OrtoMed position paper
Bibliographic record
Abstract
Sarcopenia, an age-related degenerative disorder, leads to reduced skeletal muscle mass and function, and it is associated with increased fall risk, mobility limitations, and higher mortality rates. With no approved pharmacological treatments available, physical exercise (in combination with an appropriate nutritional intervention) remains the primary approach for managing the condition. This paper reviews the evidence supporting exercise as a key treatment for sarcopenia, emphasizing the benefits of resistance, aerobic, balance, and flexibility exercises. Resistance exercise has been shown to improve muscle strength and mass, while aerobic exercise supports cardiovascular health and muscle endurance. Additionally, multimodal approaches combining exercise with nutritional interventions (such as administration of whey protein and vitamin D) have proven effective in patients with osteosarcopenia. Emerging research is highlighting molecular mechanisms, including a role for “exerkins”, signaling molecules released during physical activity, which enhance both muscle and overall health. The updated program described in this paper offers evidence-based recommendations for prescribing tailored physical activity to older adults with sarcopenia, stressing the importance of individualized exercise prescriptions based on patients’ comorbidities and fitness levels. The integration of various exercise modalities and nutritional support is critical to improving function and quality of life in this vulnerable population. KEY WORDS: Rehabilitation, physical exercise, sarcopenia, physical activity, therapeutic exercise, aging, skeletal muscle, muscle strength, muscle mass, resistance exercise.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
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".