Ultrasound-Based Sarcopenia Assessment in Pediatric Chronic Liver Disease: Correlation with Clinical Outcomes and Evaluation of a PELD-Sarcopenia Scoring Model

While adult studies have consistently shown sarcopenia to be an independent predictor of adverse outcomes, its burden and clinical relevance in pediatric chronic liver disease (pCLD) remain underexplored. The Pediatric End Stage Liver Disease (PELD) score, although widely used for prognostication and transplant prioritization, does not incorporate muscle mass or nutritional reserve, potentially underestimating disease severity in sarcopenic children.

Computed tomography based muscle quantification, the current reference standard, is limited in children due to radiation exposure and feasibility concerns. Ultrasonography offers a safe, radiation-free, bedside modality for assessing muscle mass which is a more apt tool for pediatric age group. Measurement of bilateral anterior thigh thickness (BATT), encompassing rectus femoris and vastus intermedius muscles, has shown good correlation with CT-derived muscle indices in preliminary pediatric studies, but its prognostic utility in pediatric chronic liver disease has not been systematically evaluated.

This prospective observational study aims to assess sarcopenia using ultrasound-derived BATT measurements in children less than or equal to 15 years with chronic liver disease and to examine its association with disease severity and clinical outcomes. Baseline BATT measurements and PELD scores will be obtained at enrollment, with participants followed prospectively for up to three years to record infections, hospital and ICU admissions, and mortality. Correlation and multivariate analyses will be performed to evaluate the independent impact of sarcopenia on outcomes and to explore the development of a composite PELD Sarcopenia score.

This study seeks to establish ultrasound based sarcopenia assessment as a feasible and clinically relevant prognostic tool in pediatric chronic liver disease and to determine whether integrating muscle mass parameters with existing scoring systems improves risk stratification and outcome prediction in this vulnerable population.