Myopenia and Reduced Subcutaneous Adiposity in Children With Liver Disease Are Associated With Adverse Outcomes
Bibliographic record
Abstract
BACKGROUND: Sarcopenia is defined as reduced skeletal muscle mass (SMM) or myopenia and altered muscle function and physical performance. It is unknown whether myopenia in children with end-stage liver disease (ESLD) adversely impacts clinical outcomes. We hypothesized that myopenia was prevalent in children with ESLD and related to suboptimal nutrition intake contributing to gross motor and growth delay, increased hospitalization, and medical complications. METHODS: ) and adipose tissue (total, visceral, subcutaneous adipose tissue [SAT], ) determinations at the third and fourth lumbar vertebrates during liver transplantation (LTx) assessment. ESLD children (n = 30) were age- and gender-matched to healthy controls (n = 24). Myopenia was defined as SMM index z score <-2 and low SAT was defined as SAT index z-score <-1.5. Anthropometric, biochemical, and clinical data (hospitalization, complications, growth, neurodevelopment, energy/protein intake) were collected at LTx assessment, LTx, and post LTx (first hospitalization, 6 months, 12 months). RESULTS: Four distinct body composition phenotypes in children with ESLD were found: (1) myopenia with low SAT (17%;5 of 30), (2) myopenia (3%;1 of 30), (3) low SAT (20%;6 of 30), (4) normal muscle mass and SAT (60%;18 of 30). Myopenia with low SAT was prevalent in older (>2 years), male children and was associated with gross motor delay, reduced energy intake, and increased hospitalization and infections (total/viral/fungal). CONCLUSIONS: Myopenia, accompanied by low SAT in children with ESLD, is associated with adverse clinical outcomes. Rehabilitation strategies aimed at combating myopenia in children are important.
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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 | 0.000 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".