Measurement of maximal isometric torque and muscle quality of the knee extensors and flexors in healthy 50‐ to 70‐year‐old women
Bibliographic record
Abstract
Summary Muscle quality is defined as strength per unit muscle mass. The aim of this study was to measure the maximal voluntary isometric torque of the knee extensor and flexor muscle groups in healthy older women and to develop an index of muscle quality based on the combined knee extensor and flexor torque per unit lean tissue mass (LTM) of the upper leg. One hundred and thirty‐six healthy 50‐ to 70‐year‐old women completed an initial measurement of isometric peak torque of the knee extensors and flexors (Con‐Trex MJ; CMV AG, Dubendorf, Switzerland) that was repeated 7 days later. Subsequently, 131 women returned for whole‐ and regional‐body composition analysis (iDXA™; GE Healthcare, Chalfont St Giles, Buckinghamshire, UK). Isometric peak torque demonstrated excellent within‐assessment reliability for both the knee extensors and flexors (ICC range: 0·991–1·000). Test–retest reliability was lower (ICC range: 0·777–0·828) with an observed mean increase of 5% in peak torque [6·2 (17·2) N m] on the second day of assessment (P<0·001). The relative mean decrease in combined isometric peak torque (−12·2%; P = 0·001) was double that of the relative, non‐significant, median difference in upper leg LTM (−5·3%; P = 0·102) between those in the 5th and 6th decade. The majority of difference in peak isometric torque came from the knee extensors (15·1 N m, P<0·001 versus 2·4 N m, P = 0·234). Isometric peak torque normalized for upper leg LTM (muscle quality) was 8% lower between decades (P = 0·029). These findings suggest strength per unit tissue may provide a better indication of age‐related differences in muscle quality prior to change in LTM.
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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 | 0.001 |
| 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) | 0.001 | 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".