Retrospective Study
Copyright ©The Author(s) 2015. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Aug 28, 2015; 21(32): 9614-9622
Published online Aug 28, 2015. doi: 10.3748/wjg.v21.i32.9614
Prognosis of acute-on-chronic liver failure patients treated with artificial liver support system
Pi-Qi Zhou, Shao-Ping Zheng, Min Yu, Sheng-Song He, Zhi-Hong Weng
Pi-Qi Zhou, Department of Integrated Traditional and Chinese Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, Hubei Province, China
Shao-Ping Zheng, Department of Ultrasonography, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, Hubei Province, China
Min Yu, Department of Internal Medicine, Wuhan Eleventh Hospital, Wuhan 430015, Hubei Province, China
Sheng-Song He, Zhi-Hong Weng, Department of Infectious Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, Hubei Province, China
Author contributions: Zhou PQ and Zheng SP contributed equally to this work; Weng ZH proposed the concept and designed the study; Zhou PQ and Yu M performed the study; Zheng SP and He SS analysed and interpreted the data; Zhou PQ and Zheng SP drafted the article and revised it critically for important intellectual content; and Weng ZH approved the paper to be submitted.
Supported by National Natural Science Foundation of China, No. 81201107; and Natural Science Foundation of Hubei Province of China, No. 2014CFB409.
Institutional review board statement: The study was reviewed and approved by the Institutional Review Board of Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, China.
Informed consent statement: All study participants, or their legal guardian, provided informed written consent prior to study enrollment.
Conflict-of-interest statement: All authors have not declared any conflicts of interest.
Data sharing statement: Technical appendix, statistical code, and dataset available from the corresponding author at wzh941@126.com. Participants gave informed consent for data sharing.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Correspondence to: Zhi-Hong Weng, Associate Professor, Department of Infectious Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1277 Jiefang Avenue, Wuhan 430022, Hubei Province, China. wzh941@126.com
Telephone: +86-27-85726783 Fax: +86-27-85356369
Received: April 2, 2015
Peer-review started: April 4, 2015
First decision: April 23, 2015
Revised: May 21, 2015
Accepted: July 8, 2015
Article in press: July 8, 2015
Published online: August 28, 2015
Abstract

AIM: To establish a new model for predicting survival in acute-on-chronic liver failure (ACLF) patients treated with an artificial liver support system.

METHODS: One hundred and eighty-one ACLF patients who were admitted to the hospital from January 1, 2012 to December 31, 2014 and were treated with an artificial liver support system were enrolled in this retrospective study, including a derivation cohort (n = 113) and a validation cohort (n = 68). Laboratory parameters at baseline were analyzed and correlated with clinical outcome. In addition to standard medical therapy, ACLF patients underwent plasma exchange (PE) or plasma bilirubin adsorption (PBA) combined with plasma exchange. For the derivation cohort, Kaplan-Meier methods were used to estimate survival curves, and Cox regression was used in survival analysis to generate a prognostic model. The performance of the new model was tested in the validation cohort using a receiver-operator curve.

RESULTS: The mean overall survival for the derivation cohort was 441 d (95%CI: 379-504 d), and the 90- and 270-d survival probabilities were 70.3% and 58.3%, respectively. The mean survival times of patients treated with PBA plus PE and patients treated with PE were 531 d (95%CI: 455-605 d) and 343 d (95%CI: 254-432 d), respectively, which were significantly different (P = 0.012). When variables with bivariate significance were selected for inclusion into the multivariate Cox regression model, number of complications, age, scores of the model for end-stage liver disease (MELD) and type of artificial liver support system were defined as independent risk factors for survival in ACLF patients. This new prognostic model could accurately discriminate the outcome of patients with different scores in this cohort (P < 0.001). The model also had the ability to assign a predicted survival probability for individual patients. In the validation cohort, the new model remained better than the MELD.

CONCLUSION: A novel model was constructed to predict prognosis and accurately discriminate survival in ACLF patients treated with an artificial liver support system.

Keywords: Acute-on-chronic liver failure, Artificial liver support system, Model for end-stage liver disease, Plasma exchange, Plasma bilirubin adsorption

Core tip: Liver failure has a high mortality. The current prognostic model to estimate the survival in acute-on-chronic liver failure (ACLF) patients treated with an artificial liver support system (ALSS) is not fully characterized. The aim of this study was to establish a new scoring model and to test its ability to predict the survival of ACLF patients treated with ALSS. This prognostic model accurately differentiated the outcome of ACLF patients with different risk scores and also had the ability to assign a predicted survival probability for individual patients.