Association of strength, power, and function with muscle thickness, echo intensity, and lean tissue in older males
Bibliographic record
Abstract
Dual-energy X-ray absorptiometry (DXA) appendicular lean tissue is used to screen older adults for sarcopenia. However, emerging data indicates that ageing-related muscle atrophy largely occurs within specific muscles, which may be masked using appendicular lean tissue. Comparisons between appendicular lean tissue and site-specific measures of muscle in relation to strength and physical function are needed to advance our understanding of these features in the context of poor muscle function in aged adults. Our primary objective was to compare correlations between lean tissue and site-specific muscle characteristics in relation to strength and physical function in older males. Older males (≥65 years) were evaluated for muscle strength, physical function (6-minute walk and 30-second sit-to-stand), and muscle size (appendicular and site-specific) and composition (echo intensity) using DXA and ultrasound. Of the 32 older males (75.4 ± 7.9 years), 12 had low appendicular lean tissue. All DXA and ultrasound muscle characteristics were associated (r = 0.39 to 0.83, p < 0.05) with torque or power producing capabilities. Except for the knee flexors, no differences in correlation coefficients were observed between muscle thickness or regional lean tissue in relation to muscle strength. Neither DXA nor ultrasound muscle characteristics were associated with physical function. In older males, ultrasound-based muscle thickness and DXA lean tissue provided similar associations with strength. Novelty: Lean tissue and muscle thickness provide similar associations with strength. Muscle thickness can distinguish low and normal appendicular lean tissue in older adults.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".