Age-associated changes in skeletal muscles and their effect on mobility: an operational diagnosis of sarcopenia
Bibliographic record
Abstract
Sarcopenia, the reduction of muscle mass and strength that occurs with aging, is widely considered one of the major causes of disability in older persons. Surprisingly, criteria that may help a clinician to identify persons with impaired muscle function are still lacking. Using data from a large representative sample of the general population, we examined how muscle function and calf muscle area change with aging and affect mobility in men and women free of neurological conditions. We tested several putative indicators of sarcopenia, including knee extension isometric torque, handgrip, lower extremity muscle power, and calf muscle area. For each indicator, sarcopenia was considered to be present when the measure was >2 SDs below the mean. For all four measures, the prevalence of sarcopenia increased with age, both in men and women. The age-associated gradient in prevalence was maximum for muscle power and minimum for calf-muscle area. However, lower extremity muscle power was no better than knee-extension torque or handgrip in the early identification of poor mobility, defined either as walking speed <0.8 m/s or inability to walk at least 1 km without difficulty and without developing symptoms. Optimal cutoff values that can be used in the clinical practice to identify older persons with poor mobility were developed. The findings of the study lay the basis for a cost-effective, clinical marker of sarcopenia based on a measure of isometric handgrip strength. Our findings should be verified in a longitudinal study.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".