Journal
HEPATOBILIARY & PANCREATIC DISEASES INTERNATIONAL
Volume 15, Issue 3, Pages 275-281Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/S1499-3872(16)60084-X
Keywords
liver failure; artificial liver support; plasma exchange; acute-on-chronic liver failure
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Funding
- National Science and Technology Major Project [2012ZX10002004]
- Scientific Research Fund of Zhejiang Provincial Education Department [Y201328037]
- opening foundation of the State Key Laboratory for Diagnosis and Treatment of Infectious Diseases
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, First Affiliated Hospital, Zhejiang University School of Medicine [2015KF04]
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BACKGROUND: Plasma exchange (PE)-centered artificial liver support system reduced the high mortality rate of hepatitis B virus (HBV)-related acute-on-chronic liver failure (ACLF). But the data were diverse in different medical centers. The present prospective nationwide study was to evaluate the effects of PE on patients with HBV-ACLF at different stages. METHODS: From December 2009 to December 2011, we evaluated 250 patients at different stages of HBV-ACLF from 10 major medical centers in China. All the laboratory parameters were collected at admission, before and after PE. RESULTS: Among the 250 patients who underwent 661 rounds of PE, one-month survival rate was 61.6%; 141 (56.4%) showed improvement after PE. Variables such as age (P=0.000), levels of total bilirubin (TB, P=0.000), direct bilirubin (P=0.000), total triglycerides (P=0.000), low-density lipoprotein (P=0.022), Na+ (P=0.014), Cl- (P=0.038), creatinine (Cr, P=0.007), fibrinogen (P=0.000), prothrombin time (PT, P=0.000), white blood cell (P=0.000), platelet (P=0.003) and MELD (P=0.000) were significantly related to prognosis. Multivariate logistic regression analysis showed that age, disease stage, TB, Cr and PT levels were independent risk factors of mortality among HBV-ACLF patients. CONCLUSIONS: PE can improve the clinical outcome of patients with HBV-ACLF. Levels of TB, Cr and PT, age and disease stage help to predict prognosis.
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