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Development and validation of a scoring system to predict progression to acute‐on‐chronic liver failure in patients with acute exacerbation of chronic hepatitis B
Author(s) -
Ren Yi,
Liu Lulu,
Li Ying,
Yang Fangwan,
He Yihuai,
Zhu Yanping,
Hu Xinxin,
Lin Shide
Publication year - 2018
Publication title -
hepatology research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.123
H-Index - 75
eISSN - 1872-034X
pISSN - 1386-6346
DOI - 10.1111/hepr.13062
Subject(s) - medicine , receiver operating characteristic , exacerbation , logistic regression , gastroenterology , prothrombin time , chronic hepatitis , liver disease , area under the curve , stage (stratigraphy) , immunology , virus , paleontology , biology
Aim The aim of this study was to develop and validate a scoring system to predict the progression to acute‐on‐chronic liver failure (ACLF) in patients with acute exacerbation (AE) of chronic hepatitis B (CHB). Methods The baseline characteristics of 474 patients with AE of CHB were retrospectively reviewed; 280 and 194 patients were randomly assigned to the derivation and validation cohorts, respectively. Univariate risk factors associated with ACLF development were entered into a multivariate logistic regression. The score model was established, and its predictive value was evaluated by the receiver operating characteristic (ROC) curve and the area under the ROC curve (AUROC). Results Hepatitis B virus (HBV) DNA, international normalized ratio (INR) of prothrombin time, and patient age were identified as independent risk factors associated with progressing to ACLF. The prediction model was established as R = −13.323 + 0.553 × log HBV‐DNA (copies/mL) + 3.631× INR + 0.053 × age. The AUROCs of our prediction model were higher than those of the Model for End‐stage Liver Disease (MELD) and MELD‐sodium (Na) for both cohorts. At the cut‐off value of −2.43, our prediction model had higher sensitivity (87.5%), specificity (73.6%), positive predictive value (23.0%), positive likelihood ratio (3.30), and lower negative likelihood ratio (0.17) in the validation cohort than those of MELD and MELD‐Na. Conclusion The independent risk factors associated with progressing to ACLF in patients with AE of CHB are HBV‐DNA, INR, and age. Our risk prediction model is useful for predicting the development of ACLF.