Sarcopenia: Prevalence, Mechanisms, and Functional Consequences
Bibliographic record
Abstract
Aging is associated with significant decline in neuromuscular function and performance. Sarcopenia, often defined as age-related loss of muscle mass, strength, and functional decline, is the most characteristic feature of age-related changes in the neuromuscular system. Strength decline in upper and lower limb muscles is typically 20-40% by the 7th decade and greater in older adults. This is accompanied by similar losses of limb muscle cross-sectional area. Whole body or appendicular muscle mass determination has become the method of choice for defining sarcopenia. Large population studies have reported that sarcopenia affects over 20% of 60- to 70-year-olds, and approaches 50% in those over 75 years. While loss of muscle mass explains a significant component of weakness, other factors are emerging as important contributors. In particular changes at the level of the motor neuron and motor unit are discussed. Muscle power has emerged as an important indicator of function in older adults, and we discuss knee osteoarthritis as a model of accelerated limb sarcopenia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".