AIM: The CANONIC study proposed the Chronic Liver Failure Consortium acute-on-chronic liver failure (CLIF-C ACLF) prognostic model at the European Association for the Study of the Liver-CLIF diagnosis. This study aimed to develop and validate a prognostic model for predicting the short-term mortality of hepatitis B virus (HBV) ACLF as defined by the Asia-Pacific Association for the Study of the Liver. PATIENTS AND METHODS: A retrospective cohort of 381 HBV ACLF patients and a prospective cohort of 192 patients were included in this study. Independent predictors of disease progression were determined using univariate and multivariate Cox proportional hazard regression analysis, and a regression model for predicting prognosis was established. Patient survival was estimated by Kaplan-Meier analysis and subsequently compared by log-rank tests. The area under the receiver operating characteristic curve was used to compare the performance of various current prognostic models. RESULTS: Our model was constructed with five independent risk factors: hepatic encephalopathy, international normalized ratio, neutrophil-lymphocyte ratio, age, and total bilirubin, termed as the HINAT ACLF model, which showed the strongest predictive values compared with CLIF-C ACLF, CLIF-C Organ Failure, Sequential Organ Failure Assessment, CLIF-Sequential Organ Failure Assessment, Model for End-stage Liver Disease, Model for End-stage Liver Disease-sodium, and Child-Turcotte-Pugh scores; this model reduced the corresponding prediction error rates at 28 and 90 days by 16.4-54.5% after ACLF diagnosis in both the derivation cohort and the validation cohorts. CONCLUSION: The HINAT ACLF model can accurately predict the short-term mortality of patients with HBV ACLF as defined by Asia-Pacific Association for the Study of the Liver.
AIM: The CANONIC study proposed the Chronic Liver Failure Consortium acute-on-chronic liver failure (CLIF-C ACLF) prognostic model at the European Association for the Study of the Liver-CLIF diagnosis. This study aimed to develop and validate a prognostic model for predicting the short-term mortality of hepatitis B virus (HBV) ACLF as defined by the Asia-Pacific Association for the Study of the Liver. PATIENTS AND METHODS: A retrospective cohort of 381 HBV ACLF patients and a prospective cohort of 192 patients were included in this study. Independent predictors of disease progression were determined using univariate and multivariate Cox proportional hazard regression analysis, and a regression model for predicting prognosis was established. Patient survival was estimated by Kaplan-Meier analysis and subsequently compared by log-rank tests. The area under the receiver operating characteristic curve was used to compare the performance of various current prognostic models. RESULTS: Our model was constructed with five independent risk factors: hepatic encephalopathy, international normalized ratio, neutrophil-lymphocyte ratio, age, and total bilirubin, termed as the HINAT ACLF model, which showed the strongest predictive values compared with CLIF-C ACLF, CLIF-C Organ Failure, Sequential Organ Failure Assessment, CLIF-Sequential Organ Failure Assessment, Model for End-stage Liver Disease, Model for End-stage Liver Disease-sodium, and Child-Turcotte-Pugh scores; this model reduced the corresponding prediction error rates at 28 and 90 days by 16.4-54.5% after ACLF diagnosis in both the derivation cohort and the validation cohorts. CONCLUSION: The HINAT ACLF model can accurately predict the short-term mortality of patients with HBV ACLF as defined by Asia-Pacific Association for the Study of the Liver.