A pilot feasibility study of an ultrasound-based tool to assess muscle mass in children with liver disease
Bibliographic record
Abstract
BACKGROUND: Sarcopenia is associated with adverse outcomes following liver transplantation, and at-risk children must be identified and prehabilitated. The gold standard for assessing sarcopenia in end-stage liver disease (ESLD) is CT assessment of the total Psoas Muscle Area (tPMA). However, radiation exposure and sedation requirements make this approach impractical for children. The bilateral anterior thigh thickness (BATT) is the cumulative measurement of the rectus femoris and vastus intermedius muscles by ultrasound and has been used to identify sarcopenia in adults. There are no studies assessing muscle mass in children using ultrasound. We hypothesized that measuring BATT with ultrasound in children with ESLD is feasible and is associated with sarcopenia. METHODS: A prospective pilot feasibility study of patients with ESLD on the liver transplantation waitlist and age-matched healthy controls. BATT was measured by a single operator using ultrasound. tPMA indices were determined by CT imaging, along with clinical and anthropometric data. RESULTS: Thirty children were studied between September 2021 and December 2022, 15 listed patients aged 4-30 months, and 15 controls aged 4-32 months. No major technical challenges or complications were encountered while performing the ultrasounds. Median BATTs of 30.8 mm (interquartile range: 27.9-32.8 mm) versus 32.7 mm (interquartile range: 31.8-36.9 mm) were demonstrated in the ESLD and control groups, respectively, and p = 0.01. A positive correlation (R = 0.603) was demonstrated between BATT and tPMA at the L4-5 level among patients with ESLD. No correlation was observed between BATT and anthropometrics. CONCLUSIONS: This study yields novel data on the feasibility of ultrasound to measure mid-thigh thickness in children with ESLD and suggests a correlation between BATT and tPMA, the gold standard for diagnosing sarcopenia. It sets the stage for ultrasound as a simple, noninvasive, and easily repeatable tool for assessing sarcopenia in children.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".