Estimation of skeletal muscle mass in 4-year-old children using the D3-creatine dilution method
Bibliographic record
Abstract
Abstract Background Given limited experience in applying the creatine-(methyl-D3) (D3Cr) dilution method to measure skeletal muscle mass (SMM) in young children, the feasibility of deployment in a fielding setting and performance of the method was assessed in a cohort of 4-year-old children in Dhaka, Bangladesh. Methods Following D3Cr oral dose (10 mg) administration, single fasting urine samples were collected at 2–4 days (n = 100). Twenty-four-hour post-dose collections and serial spot urine samples on days 2, 3 and 4 were obtained in a subset of participants (n = 10). Urinary creatine, creatinine, D3Cr and D3-creatinine enrichment were analyzed by liquid chromatography–tandem mass spectrometry. Appendicular lean mass (ALM) was measured by dual-energy x-ray absorptiometry and grip strength was measured by a hand-held dynamometer. Results SMM was measured successfully in 91% of participants, and there were no adverse events. Mean ± SD SMM was greater than ALM (4.5 ± 0.4 and 3.2 ± 0.6 kg, respectively). Precision of SMM was low (intraclass correlation = 0.20; 95% CI: 0.02, 0.75; n = 10). Grip strength was not associated with SMM in multivariable analysis (0.004 kg per 100 g of SMM; 95% CI: −0.031, 0.038; n = 91). Conclusions The D3Cr dilution method was feasible in a community setting. However, high within-child variability in SMM estimates suggests the need for further optimization of this approach. Impact The D3-creatine (D3Cr) stable isotope dilution method was considered a feasible method for the estimation of skeletal muscle mass (SMM) in young children in a community setting and was well accepted among participants. SMM was weakly associated with both dual-energy x-ray absorptiometry-derived values of appendicular lean mass and grip strength. High within-child variability in estimated values of SMM suggests that further optimization of the D3Cr stable isotope dilution method is required prior to implementation in community research settings.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".