Sarcopenia in Children Post Liver Transplant: Development of a Home‐Based Video Program to Support Muscle Strength and Function—A Pre–Post Controlled Pilot Study
Bibliographic record
Abstract
INTRODUCTION: Sarcopenia is common in children after liver transplantation (LTx). Resistance training (RT) may be effective in combating sarcopenia. OBJECTIVES: The purpose of the study was to test the feasibility and impact of a 12-week RT program on skeletal muscle mass (SMM), muscle strength, physical performance (PP), and child-parent perspectives about RT. METHODS: Children (6-18 years) post-LTx and healthy controls (HC) underwent progressive RT using resistance bands. SMM and adipose tissue (MRI: abdomen and thigh), muscle strength (handgrip, push-ups, sit-to-stand), and PP (6-minute walk test [6MWT], timed-up-and-down-stair test [TUDS]) were measured before and after 12-weeks of RT. RESULTS: Ten children post-LTx (11.9 ± 3.5 years) and 13 HC (11.7 ± 3.9 years) participated. LTx children significantly increased abdominal SM-index (+4.6% LTx vs. a -2.7% HC; p = 0.01) and decreased visceral adipose tissue-index (-18% LTx vs. -0.8% HC; p = 0.04) compared to HC. No thigh SMI changes were noted. Significant increases in 6MWT distance (LTx; p = 0.04), number of push-ups (p = 0.04), and greater reduction times for TUDS (-10.6% vs. +1.7%; p = 0.05) occurred after 12 weeks. Higher thigh muscle-fat content was associated with worse physical performance. These results were impacted by adherence (≥75% vs. <75%) and family engagement. CONCLUSIONS: RT in children post-LTx is feasible and effective. RT in children post-LTx may alleviate adverse outcomes associated with sarcopenia.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".