The Association of Muscle Mass Measured by D3-Creatine Dilution Method With Dual-Energy X-Ray Absorptiometry and Physical Function in Postmenopausal Women
Bibliographic record
Abstract
BACKGROUND: The D3-creatine (D3Cr) dilution method provides a direct measure of skeletal muscle. The aim of this study was to compare the association of D3Cr muscle mass with lean body mass (LBM) measured by dual-energy x-ray absorptiometry (DXA) and examine its relation with physical function in postmenopausal women. METHODS: Seventy-four community-dwelling women (mean age 82.3 ± 5.4) participated in this pilot study from the Buffalo, New York clinical site of the Women's Health Initiative (WHI). Participants attended a clinic visit which included anthropometric measures, blood draw, DXA scan, measures of physical function, and initiated the D3Cr protocol. Physical function was evaluated using hand grip strength, short physical performance battery (SPPB), and RAND-36 physical function scale. Descriptive statistics and logistic regression models were used to examine the associations of D3Cr muscle mass with functional outcomes. RESULTS: D3-creatine muscle mass was moderately correlated with DXA LBM (r = 0.50) and DXA appendicular lean mass (ALM) (r = 0.50). Individuals with high D3Cr muscle mass (%) had higher physical function compared to individuals with low muscle mass (%), indicated by high scores on SPPB (odds ratio [OR] = 5.24; 95% confidence interval [CI]: 1.40, 19.58). We observed stronger relationships between high D3Cr and physical function than either DXA LBM (OR = 3.40; 95% CI: 0.88, 13.11) or DXA ALM (OR = 4.15; 95% CI: 1.10, 15.68) and physical function. CONCLUSIONS: Our findings provide strong preliminary data for the associations of D3Cr muscle mass with measures of physical function in older women. These findings support and extend prior work on D3Cr muscle mass in older men.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".