Research Papers:
A novel dynamic model for predicting outcome in patients with hepatitis B virus related acute-on-chronic liver failure
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Abstract
Ran Xue1,*, Zhonghui Duan1,*, Haixia Liu1, Li Chen2, Hongwei Yu1, Meixin Ren1, Yueke Zhu1, Chenggang Jin3, Tao Han4, Zhiliang Gao5 and Qinghua Meng1
1Department of Critical Care Medicine of Liver Disease, Beijing You-An Hospital, Capital Medical University, Beijing, China
2Georgia Prevention Institute, Medical College of Georgia, Augusta University, Augusta, GA, USA
3The School of Social Development and Public Policy, Beijing Normal University, Beijing, China
4Department of Hepatology, Tianjin Third Central Hospital of Tianjin Medical University, Tianjin, China
5Department of Infectious Diseases, The Third Affiliated Hospital, Zhongshan University, Guangzhou, China
*These authors have contributed equally to this work
Correspondence to:
Qinghua Meng, email: [email protected]
Keywords: acute-on-chronic liver failure; hepatitis B; prognostic model
Received: October 06, 2017 Accepted: October 27, 2017 Published: November 14, 2017
ABSTRACT
Aim: It is challenging to predict the outcome of patients with hepatitis B virus related acute-on-chronic liver failure (HBV-ACLF) through existing prognostic models. Our aim was to establish a novel dynamic model to improve the predictive efficiency of 30-day mortality in HBV-ACLF patients.
Methods: 305 patients who were diagnosed as HBV-ACLF (derivation cohort, n=211; validation cohort, n=94) were included in this study. The HBV-ACLF dynamic (HBV-ACLFD) model was constructed based on the daily levels of predictive variables in 7 days after diagnosis combined with baseline risk factors by multivariate logistic regression analysis. The HBV-ACLFD model was compared with the Child-Turcotte-Pugh (CTP) score, end-stage liver disease (MELD) score, and MELD within corporation of serum sodium (MELD-Na) score by the area under the receiver-operating characteristic curves (AUROC).
Results: The HBV-ACLFD model demonstrated excellent discrimination with AUROC of 0.848 in the derivation cohort and of 0.813 in the validation cohort (p=0.620). The performance of the HBV-ACLFD model appeared to be superior to MELD score, MELD-Na score and CTP score (P<0.0001).
Conclusion: The HBV-ACLFD model can accurately predict 30-day mortality in patients with HBV-ACLF, which is helpful to select appropriate clinical procedures, so as to relieve the social and economic burden.
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