• Linxiang Liu, Peng Chen, Nanxi Xiao, Qi Liu, and Xuan Zhu.
• Department of Gastroenterology, The First Affiliated Hospital of Nanchang University, Nanchang, China.
• Ann. Med. 2023 Jan 1; 55 (2): 22877082287708.

BackgroundAcute-on-chronic liver failure (ACLF) is a distinctive and severe syndrome, marked by an excessive systemic inflammatory response. In vivo, interleukin 8 (IL-8) is an essential pro-inflammatory cytokine. We aimed to investigate the value of serum IL-8 levels in predicting mortality in ACLF patients in the background of hepatitis B virus-related cirrhosis.MethodsIn this study, we conducted a retrospective analysis of the clinical baseline characteristics of 276 patients with ACLF in the context of HBV-related cirrhosis. Logistic regression analysis was employed to identify independent risk factors for short-, intermediate-, and long-term mortality. Using these independent risk factors, we developed a nomogram model, which was subsequently validated. To assess the clinical usefulness of the nomogram model, we performed decision curve analysis (DCA).ResultsOut of the 276 patients with ACLF, 98 (35.5%), 113 (40.9%), and 128 (46.4%) died within 28, 90, and 180 days, respectively. Serum IL-8 levels were only an independent predictor of 28-day mortality and could simply classify ACLF patients. Conversely, mean arterial pressure (MAP), HBV-DNA, and COSHACLF IIs were independent predictors of mortality across all three observation periods. We constructed a nomogram based on IL-8 that was able to visualise and predict 28-day mortality with a C-index of 0.901 (95% CI: 0.862-0.940). Our calibration curves, Predicted Probability of Death & Actual Survival Status plot, and Confusion Matrix demonstrated the nomogram model's strong predictive power. DCA indicated the nomogram's promising clinical utility in predicting 28-day mortality in ACLF patients.ConclusionSerum IL-8 levels predict short-term mortality in ACLF patients in the background of HBV-associated cirrhosis, and the developed Nomogram model has strong predictive power and good clinical utility.

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