A Novel Systemic Inflammation-Based Model for Predicting Mortality in HBV-Related ACLF

Area of Science:

• Hepatology
• Immunology
• Biomarker Research

Background:

• Hepatitis B virus (HBV)-related acute-on-chronic liver failure (ACLF) is linked to severe inflammation and immune dysregulation, leading to poor prognosis.
• The prognostic value of the C-reactive protein to lymphocyte ratio (CLR), an inflammatory biomarker, remains underexplored in HBV-ACLF.

Purpose of the Study:

• To evaluate the utility of the CLR and other clinical parameters in predicting disease progression and short-term mortality in HBV-ACLF patients.
• To develop and validate a predictive model for risk stratification in HBV-ACLF.

Main Methods:

• A retrospective cohort study involving 639 hospitalized HBV-ACLF patients, divided into training (447 cases) and validation (192 cases) sets.
• Logistic regression analysis was used to identify independent risk factors and construct the predictive XY-model.
• APASL criteria were used for HBV-ACLF diagnosis.

Main Results:

• The C-reactive protein to lymphocyte ratio (CLR) was identified as a significant independent risk factor for disease progression in HBV-ACLF (OR 1.02, 95% CI 1.01-1.04, p<0.05).
• Factors including liver cirrhosis, age, CLR, serum total bilirubin, calcium, prothrombin activity, and alpha fetoprotein significantly influenced HBV-ACLF prognosis.
• The developed seven-predictor model demonstrated accuracy in predicting short-term mortality.

Conclusions:

• The CLR is a valuable prognostic biomarker for assessing disease progression in HBV-ACLF.
• The novel predictive model incorporating CLR and other clinical factors offers a promising tool for guiding clinical management of HBV-ACLF, particularly in Asian populations.