RESUMO
BACKGROUND: Patients with acute-on-chronic liver failure (ACLF) precipitated by hepatic injury and extrahepatic insults had distinct clinical phenotypes, and prognosis. This study aimed to validate prognostic models for ACLF and to explore their discriminative abilities in ACLF population categorized by the etiologies of precipitating events. METHODS: This study collected data from 343 consecutive cirrhotic patients hospitalized with the diagnosis of ACLF according to the EASL-CLIF-Consortium definition. The discrimination abilities of prognostic models at the onset of ACLF were tested with the concordance index and area under the receiver operating characteristic curve. RESULTS: Among the entire cohort, 103 patients survived with medical management, nine patients were transplanted, and 231 patients died without liver transplantation. The predictive accuracy of the Chronic Liver Failure-Sequential Organ Failure Assessment (CLIF-SOFA) for 28-day mortality was similar to the CLIF Consortium Organ Failure (CLIF-C OF) but significantly higher than the CLIF Consortium ACLF, the Child-Turcotte-Pugh, the model for end-stage liver disease (MELD), the MELD-sodium, the integrated MELD, and the Acute Physiology and Chronic Health Evaluation II. Of note, 44 patients had acute hepatic insult triggering ACLF (hepatic-ACLF), 244 were exclusively precipitated by bacterial infection or gastrointestinal bleeding (extrahepatic-ACLF), and 55 cases had no any identifiable potential precipitating events. Patients with hepatic-ACLF had significantly higher 28-day mortality than extrahepatic-ACLF patients. The CLIF-SOFA and CLIF-C OF displayed the highest accuracy significantly outperforming other scoring systems in predicting mortality among patients with hepatic-ACLF and those with extrahepatic-ACLF. CONCLUSION: The CLIF-SOFA and simpler CLIF-C OF are reliable measures of mortality risk in ACLF patients precipitated by either hepatic or extrahepatic insults. Both validated models could be used to stratify the risk of death and improve management of ACLF.
