Digital twins in pediatric metabolic dysfunction-associated steatotic liver disease: Developmentally referenced multimodal risk stratification

Table 2 Evidence hierarchy for claims in this review

Evidence tier	Evidence source	What it supports in this review	What it does not establish	Ref.
Tier 1: Direct	Pediatric MASLD	Candidate clinical variables, observed associations, epidemiology, ALT/histology limitations, imaging, body composition, genetics, cardiometabolic outcomes, microbiome, and social context	A validated pediatric MASLD digital twin; calibrated individualized twin-based risk; adaptive follow-up benefit; causal treatment-effect simulation	[2-10,33-44,57-61]
Tier 2: Extrapolated	Adult MASLD or metabolic disease	Biological plausibility, adult feasibility of digital-twin-enabled metabolic management, and selected adult prognostic or genetic concepts	Pediatric calibration, safety, developmental validity, or pediatric treatment effects	[21,30,31,46,56]
Tier 3: Pediatric extrapolation	Other pediatric diseases/child-health digital twins	Developmental referencing, pediatric digital-twin feasibility, family perspectives, ethics, and child-centered implementation principles	MASLD-specific predictive performance or clinical utility	[11,22-27]
Tier 4: Methodological	Generic digital twins, AI, prediction-model methods, regulation, and interoperability	Definitions, architecture, explainability, federated learning, validation/reporting methods, governance, interoperability, and regulatory principles	Clinical validity or effectiveness in pediatric MASLD	[12-20,28,29,32,62-82]

Evidence tiers reflect directness to pediatric metabolic dysfunction-associated steatotic liver disease (MASLD) digital-twin clinical use, not an assessment of study quality. Evidence from Tiers 2-4 is extrapolative and should not be interpreted as validation of pediatric MASLD digital-twin outputs. AI: Artificial intelligence; ALT: Alanine aminotransferase; MASLD: Metabolic dysfunction-associated steatotic liver disease.