Literature DB >> 22481448

Different models in predicting the short-term prognosis of patients with hepatitis B virus-related acute-on-chronic liver failure.

Wen-Bin Yang1, En-Qiang Chen, Hong-Xia Bi, Lang Bai, Xue-Bin Chen, Ping Feng, Hong Tang.   

Abstract

BACKGROUND AND AIMS: Effective assessing the prognosis of patients with end-stage liver disease is always challenging. This study aimed to investigate the accuracy of different models in predicting short-term prognosis of patients with hepatitis B virus (HBV)-related acute-on-chronic liver failure (ACLF).
MATERIAL AND METHODS: We retrospectively evaluated survival of a cohort of patients with at least 3-month follow up. The receiver-operating-characteristic curves (ROC) were drawn for Child-Turcotte-Pugh (CTP) classification, King's College Hospital (KCH) criteria, model for end-stage liver disease (MELD), MELD combined with serum sodium (Na) concentration (MELDNa), integrated MELD (iMELD) and logistic regression model (LRM).
RESULTS: Of the 273 eligible patients, 152 patients (55.7%) died within 3-month follow up. In cirrhotic patients (n = 101), the AUCs of LRM (0.851), MELDNa (0.849), iMELD (0.845) and MELD (0.840) were all significantly higher than those of KCH criteria (0.642) and CTP (0.625) (all p < 0.05), while the differences among LRM, MELD, MELDNa and iMELD were not significant, and the most predictive cutoff value was 0.5176 for LRM, 30 for MELDNa, 47.87 for iMELD and 29 for MELD, respectively. In non-cirrhotic patients (n = 172), the AUC of LRM (0.897) was significantly higher than that of MELDNa (0.776), iMELD (0.768), MELD (0.758), KCH criteria (0.647) and CTP (0.629), respectively (all p < 0.05), and the most predictive cutoff value for LRM was -0.3264.
CONCLUSIONS: LRM, MELD, MELDNa and iMELD are with similar accuracy in predicting the shortterm prognosis of HBV-ACLF patients with liver cirrhosis, while LRM is superior to MELD, MELDNa and iMELD in predicting the short-term prognosis of HBV-ACLF patients without liver cirrhosis.

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Year:  2012        PMID: 22481448

Source DB:  PubMed          Journal:  Ann Hepatol        ISSN: 1665-2681            Impact factor:   2.400


  10 in total

1.  Prognosis of acute-on-chronic liver failure patients treated with artificial liver support system.

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2.  Nucleoside analogs prevent disease progression in HBV-related acute-on-chronic liver failure: validation of the TPPM model.

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Review 3.  Early warning and clinical outcome prediction of acute-on-chronic hepatitis B liver failure.

Authors:  En-Qiang Chen; Fan Zeng; Ling-Yun Zhou; Hong Tang
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4.  Liver failure determines the outcome in patients of acute-on-chronic liver failure (ACLF): comparison of APASL ACLF research consortium (AARC) and CLIF-SOFA models.

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Journal:  Hepatol Int       Date:  2017-08-30       Impact factor: 6.047

5.  Asian-Pacific clinical practice guidelines on the management of hepatitis B: a 2015 update.

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7.  Complications constitute a major risk factor for mortality in hepatitis B virus-related acute-on-chronic liver failure patients: a multi-national study from the Asia-Pacific region.

Authors:  Tao Chen; Zhongyuan Yang; Ashok Kumar Choudhury; Mamun Al Mahtab; Jun Li; Yu Chen; Soek-Siam Tan; Tao Han; Jinhua Hu; Saeed S Hamid; Lee Guan Huei; Hasmik Ghazinian; Yuemin Nan; Yogesh K Chawla; Man-Fung Yuen; Harshad Devarbhavi; Akash Shukla; Zaigham Abbas; Manoj Sahu; A K Dokmeci; Laurentias A Lesmana; Cosmas Rinaldi A Lesmana; Shaojie Xin; Zhongping Duan; Wei Guo; Ke Ma; Zhongwei Zhang; Qiuyu Cheng; Jidong Jia; B C Sharma; Shiv Kumar Sarin; Qin Ning
Journal:  Hepatol Int       Date:  2019-10-24       Impact factor: 6.047

8.  Predictive Value of Blood Ammonia in the Prognosis of Acute Liver Failure Evaluated by Receiver Operating Characteristic Curves.

Authors:  Lei Li; Peng Liu; Ke Li; Fang Lin; Cheng-Cheng Ji; Yong-Gang Wang; Biao Xu; Jin-Song Mu; Yue-Su Zhou
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9.  Establishment and validation of ALPH-Q score to predict mortality risk in patients with acute-on-chronic hepatitis B liver failure: a prospective cohort study.

Authors:  Sheng-Jie Wu; Hua-Dong Yan; Zai-Xing Zheng; Ke-Qing Shi; Fa-Ling Wu; Yao-Yao Xie; Yu-Chen Fan; Bo-Zhi Ye; Wei-Jian Huang; Yong-Ping Chen; Ming-Hua Zheng
Journal:  Medicine (Baltimore)       Date:  2015-01       Impact factor: 1.889

10.  Logistic regression model can reduce unnecessary artificial liver support in hepatitis B virus-associated acute-on-chronic liver failure: decision curve analysis.

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  10 in total

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