Sarcopenia in Children With End‐Stage Liver Disease
Bibliographic record
Abstract
BACKGROUND: Sarcopenia, reflected by decreased psoas muscle surface area (PMSA), has been identified as a novel and independent predictor of wait-list mortality and outcomes in adult liver transplantation (LT). We hypothesized that children with end-stage liver disease (ESLD) would have smaller PMSA than healthy controls. METHODS: Computer tomography images of children (ages 0 to 18 years) listed for LT in 2015 and a control group comprised 2:1 age- and gender-matched healthy pediatric trauma victims were reviewed. PMSA was determined at 2 intervertebral disc (L3/4; L4/5) levels. A subset of images was reviewed by 2 radiologists to determine interrater correlation. RESULTS: A total of 23 children with ESLD were included, and the most prevalent diagnosis was biliary atresia (61%). On both lumbar levels, median PMSA was significantly smaller in ESLD subjects compared with the 46 healthy controls (L4/5; median total PMSA (tPMSA) 407 mm (interquartile range 339-537) versus controls 513 mm (interquartile range 437-672); P = 0.004), independent of participants' weight z scores (r = 0.01; P = 0.95). Excellent interrater correlation was seen (intraclass correlation 0.99). CONCLUSIONS: In this retrospective pilot study, PMSA was significantly lower in children with ESLD compared with healthy age- and gender-matched controls. Because this finding was independent of growth in ESLD subjects, PMSA may represent a novel objective nutritional biomarker in children with advanced liver disease.
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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) | 0.000 | 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 | 0.001 |
| 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".