Affiliation:
1. The General Hospital of Western Theater Command
2. Fudan University
Abstract
Abstract
Background: Type C hepatitis B-related acute-on-chronic liver failure (HBV-ACLF), which based on decompensated cirrhosis, have different laboratory tests, precipitating events, organ failure and clinical outcome. The predictors of prognosis for the type C HBV-ACLF patients are different from other subgroups. This study aimed to construct a novel, short-term prognostic score that applied serological indicators of hepatic regeneration and noninvasive assessment of liver fibrosis to predict outcomes in patients with type C HBV-ACLF.
Method: Patients with type C HBV-ACLF were observed for 90 days. Demographic information, clinical examination, and laboratory test results of the enrolled patients were collected. Univariate and multivariate Logistic regression was performed to identify independent prognostic factors and develop a novel prognostic scoring system. And a receiver operating characteristic (ROC) curve was used to analyze the performance of the model.
Results: A total of 224 patients with type C HBV-ACLF were finally incorporated. The overall survival rate within 90 days was 47.77 %. Age, total bilirubin (TBil), international normalized ratio (INR), alpha-fetoprotein (AFP), white blood cell (WBC), serum natrium (Na), and Aspartate aminotransferase/platelet ratio index (APRI) were found to be independent prognostic factors. According to the results of the Logistic regression analysis, a new prognostic model (we named it the A3Twin score) was established. The area under the curve (AUC) of the receiver operating characteristic curve (ROC) was 0.851[95% CI(0.801-0.901)], the sensitivity of 78.8%, and specificity of 71.8%,which was significantly higher than that of the MELD, IMELD,MELD-Na, TACIA and COSSH‐ACLF II scores (all P < 0.001).Patients with lower A3Twin scores (<-9.07) would survive longer.
Conclusions: A new prognostic scoring system for patients with type C HBV-ACLF based on seven routine indexes was established in our study, and can accurately predict short-term mortality and might be used to guide clinical management.
Publisher
Research Square Platform LLC