Multi-algorithm consensus classification identifies three distinct acute liver failure subtypes with differential treatment responses: a multi-database cohort study

• We developed a novel Multi-algorithm Consensus-based Acute Liver Failure Classification (MCALFC) approach that identifies three clinically distinct acute liver failure subtypes with different pathophysiological profiles, prognoses, and treatment responses. • Our study validates these subtypes across five independent critical care databases (MIMIC-III CareVue, eICU, HiRID, NWICU, and SICdb), demonstrating the robustness and generalizability of our classification approach across diverse international healthcare systems. • We identified subtype-specific treatment responses, with epinephrine showing protective effects in cardiovascular dysfunction and hyperacute hepatic necrosis subtypes but harmful effects in critical hemodynamic collapse subtype, while dexmedetomidine demonstrated significant benefits only in the hyperacute hepatic necrosis subtype. • The “hyperacute hepatic necrosis” subtype (Subtype 3) showed preserved hemodynamics but severe hepatocellular injury, with unique treatment response patterns including poor tolerance to renal replacement therapy, indicating the importance of targeted approaches for patients with primary hepatic injury. • Our findings provide a foundation for precision medicine in acute liver failure management, potentially improving patient outcomes through personalized therapeutic strategies based on subtype classification and challenging the current one-size-fits-all treatment paradigm. Acute liver failure (ALF) is a heterogeneous syndrome with high mortality. Current prognostic models fail to capture pathophysiological heterogeneity, necessitating refined patient stratification and personalized therapeutic strategies. We analyzed 2,691 adult patients with ALF from six international critical care databases (MIMIC-IV as discovery cohort, n = 1,227; five validation cohorts: MIMIC-III CareVue, eICU, HiRID, NWICU, and SICdb, n = 1,464). We developed a Multi-algorithm Consensus-based Acute Liver Failure Classification (MCALFC) approach integrating ten clustering algorithms to identify distinct subtypes based on clinical parameters, interventions, comorbidities, and medications. We validated these subtypes across databases, performed survival analyses, conducted SHAP analysis using XGBoost to identify key distinguishing features, and evaluated treatment response heterogeneity. Three robust ALF phenotypes emerged: Subtype 1 (28.3 %) − “critical hemodynamic collapse” with severe cardiovascular instability (MAP 78.9 mmHg, HR 113.5 bpm), highest illness severity (SAPS II: 62.0, SOFA: 12.2), and organ support requirements; Subtype 2 (44.6 %) − “cardiovascular dysfunction” with profound hypotension (MAP 69.1 mmHg) but low heart rate (84.3 bpm); and Subtype 3 (27.0 %) − “hyperacute hepatic necrosis” with preserved hemodynamics (MAP 99.4 mmHg) but severe hepatocellular injury (ALT 1059.8 U/L, AST 1427.3 U/L). Subtypes demonstrated distinct survival trajectories maintained through one-year follow-up (28-day mortality: Subtype 2 HR 0.48, 95 % CI: 0.40–0.59; Subtype 3 HR 0.39, 95 % CI: 0.31–0.50 vs. Subtype 1). Treatment responses varied significantly: epinephrine was harmful in Subtype 1 (OR 1.68) but protective in Subtypes 2 and 3 (OR 0.47, 0.34); dexmedetomidine benefited Subtype 3 (OR 0.26) but harmed Subtype 2 (OR 1.47); renal replacement therapy showed highest risk in Subtype 3 (OR 2.05). ALF comprises three distinct phenotypes with unique pathophysiological features, prognostic trajectories, and treatment responses. This phenotypic classification, validated across multiple international databases, provides a framework for precision medicine in ALF management and challenges the current one-size-fits-all treatment paradigm.