Abstract
BACKGROUND: This study aimed to develop and validate a novel nomogram that incorporates the neutrophil percentage-to-albumin ratio (NPAR) for predicting 30-day and 90-day unfavorable outcomes in acute-on-chronic liver failure (ACLF) patients. METHODS: We retrospectively enrolled 641 ACLF patients from the First Affiliated Hospital of Anhui Medical University between January 2017 and June 2024, randomly assigning them to training (n = 448) and validation (n = 193) cohorts. Univariate Cox regression, the Least Absolute Shrinkage and Selection Operator (LASSO) regression, and multivariate Cox analysis identified seven independent predictors: bacterial infection, hepatic encephalopathy, age, prothrombin time (PT), total bilirubin (TBIL), lymphocyte count, and NPAR. RESULTS: The nomogram demonstrated superior predictive performance in the training cohort, with area under the curve (AUC) values of 0.874 (95% CI 0.838-0.910) and 0.877 (95% CI 0.845-0.909) for 30-day and 90-day outcomes, respectively, and a concordance index (C-index) of 0.825 (95% CI 0.796-0.853), significantly outperforming the MELD, MELD-Na, CLIF-C ACLFs and COSSH-ACLF II scores. Calibration curves showed strong concordance between predicted and observed survival probabilities, and decision curve analysis confirmed broad clinical applicability. We have also validated the predictive value of the new model for ACLF in a validation cohort (n = 193). Compared with COSSH-ACLF II, the model exhibited significant improvements in net reclassification index (NRI) and integrated discrimination improvement (IDI) (P < 0.001). Risk stratification effectively categorized patients into low-, intermediate-, and high-risk groups, revealing varied survival rates. In addition, a user-friendly dynamic web-based calculator was developed. CONCLUSIONS: This nomogram that integrates inflammatory and nutritional indicators provides a high-precision tool for short-term prognosis assessment in ACLF patients and is expected to guide clinical management.