A Systemic Inflammation Response Index (SIRI)-based nomogram for predicting the prognosis of hepatitis B virus-related acute-on-chronic liver failure: a retrospective cohort study

OBJECTIVE : Systemic inflammatory response is closely linked to the development and prognosis of liver failure. This study aimed to establish a prognostic model incorporating inflammatory markers, including the systemic inflammation response index (SIRI), defined as neutrophil count × monocyte count / lymphocyte count, to assess outcomes in patients with hepatitis B virus–related acute-on-chronic liver failure (HBV-ACLF). METHODS : A retrospective analysis was conducted on HBV-ACLF patients admitted to Mengchao Hepatobiliary Hospital of Fujian Medical University from January 2019 to December 2022. Patients were classified by 28-day and 90-day outcomes. Baseline clinical data, hematologic, biochemical, and coagulation parameters were collected. Univariate logistic regression was first performed, followed by multivariate logistic regression with a backward stepwise approach. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis. RESULTS : A total of 321 patients (86.6% male; mean age 46.21 ± 12.46 years) were included, with 28-day and 90-day mortality rates of 16.51% and 24.92%. Non-survivors were older and had higher SBP, SIRI, Cr, BUN, INR, and higher rates of hypertension, decompensated cirrhosis, hepatic encephalopathy, and bacterial infection (all P < 0.05). Multivariate analysis identified SBP, SIRI, Cr, BUN, and INR as independent predictors of both outcomes, while age, lower HDL, and LDL were additionally associated with 90-day mortality. Nomograms showed good calibration and discrimination (AUCs 0.866 and 0.897) and high clinical utility. SIRI remained independently associated with mortality after full adjustment. CONCLUSION : SIRI is significantly associated with the risk of HBV-ACLF mortality, and the nomogram provides an objective tool for identifying high-risk patients and supporting individualized management.