Beyond weight loss: Predicting and personalizing liver outcomes after metabolic-bariatric surgery in metabolic dysfunction-associated steatotic liver disease

Metabolic dysfunction-associated steatotic liver disease (MASLD) is common among individuals with severe obesity.Metabolic-bariatric surgery improves steatosis and steatohepatitis and is associated with fibrosis regression in many patients; however, hepatic response is heterogeneous, and long-term biopsy data remain limited.This review examines metabolic-bariatric surgery in MASLD from a precision-medicine perspective, focusing on which patients derive hepatic benefit, the magnitude of that benefit, and its durability.We synthesize evidence on clinical stage, non-invasive tests, weight and diabetes trajectories, adipokines, genetics, the gut-liver and thyroid-liver axes, multi-omics, and artificial intelligence.Most proposed predictors reflect baseline disease severity or biological plausibility rather than validated surgery-specific prediction.We therefore present a tiered predict-personalize-monitor framework as a hypothesis-generating research model rather than a clinical algorithm.Routine variables and basic non-invasive tests comprise the essential tier; elastography and magnetic resonance methods are optional advanced tools; genetics, multi-omics, and machine learning remain research tools.Prospective external validation is required before this framework can inform individual treatment allocation or postoperative pharmacotherapy.