Development and Validation of a New Prognostic Model for Predicting Survival Outcomes in Patients with Acute-on-chronic Liver Failure.

Abstract

Background and aims: Early determination of prognosis in patients with acute-on-chronic liver failure (ACLF) is crucial for optimizing treatment options and liver allocation. This study aimed to identify risk factors associated with ACLF and to develop new prognostic models that accurately predict patient outcomes.

Methods: We retrospectively selected 1,952 hospitalized patients diagnosed with ACLF between January 2010 and June 2018. This cohort was used to develop new prognostic scores, which were subsequently validated in external groups.

Results: The study included 1,386 ACLF patients and identified six independent predictors of 28-day mortality through multivariate analysis (all p < 0.05). The new score, based on a multivariate regression model, demonstrated superior predictive accuracy for both 28-day and 90-day mortalities, with Areas under the ROC curves of 0.863 and 0.853, respectively (all p < 0.05). This score can be used to stratify the risk of mortality among ACLF patients with ACLF, showing a significant difference in survival between patients categorized by the cut-off value (log-rank (Mantel-Cox) χ² = 487.574 and 606.441, p = 0.000). Additionally, the new model exhibited good robustness in two external cohorts.

Conclusions: This study presents a refined prognostic model, the Model for end-stage liver disease-complication score, which accurately predicts short-term mortality in ACLF patients. This model offers a new perspective and tool for improved clinical decision-making and short-term prognostic assessment in ACLF patients.