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      Scoring systems for prediction of mortality in decompensated liver cirrhosis: A meta-analysis of test accuracy

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          Abstract

          AIM

          To compare the accuracy of the scoring systems Child-Turcotte-Pugh (CTP), Model for End-stage Liver Disease score (MELD), MELD-Na, and MELD to Serum Sodium ratio (MESO) to predict the mortality in decompensated liver cirrhosis.

          METHODS

          The PubMed, Web of Science, Cochrane Library, EMBASE, and Ovid databases were systematically searched from inception to September 2018 for relevant articles, and we evaluated the quality of the included studies. The accuracy of scoring systems was analyzed with Stata 12 and MetaDiSc 1.4.

          RESULTS

          Sixteen studies involving 2337 patients were included. The pooled areas under the summary receiver operating characteristic curves (AUROCs) of CTP, MELD, MELD-Na, and MESO to predict mortality were 0.81, 0.78, 0.85, and 0.86, respectively. Within 3 mo, the AUROCs of CTP, MELD, and MELD-Na in predicting mortality were 0.78, 0.76, and 0.89, respectively. The AUROCs of CTP, MELD, and MELD-Na at 3 mo were 0.86, 0.78, and 0.86, respectively. The AUROCs of CTP, MELD, and MELD-Na at 6 mo were 0.91, 0.83, and 0.90, respectively. The AUROCs of CTP, MELD, and MELD-Na at 12 mo were 0.72, 0.75 and 0.84, respectively. In cirrhotic patients with bleeding, the AUROCs of CTP and MELD were 0.76 and 0.88, respectively.

          CONCLUSION

          MESO has the highest AUROC in all assessed scoring systems. Considering the different time points, MELD-Na has good accuracy in predicting the mortality of decompensated liver cirrhosis. Compared to CTP, MELD is better in predicting variceal bleeding.

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          Most cited references40

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          Transection of the oesophagus for bleeding oesophageal varices.

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            Child–Pugh Versus MELD Score for the Assessment of Prognosis in Liver Cirrhosis

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              The new liver allocation system: moving toward evidence-based transplantation policy.

              In 1999, the Institute of Medicine suggested that instituting a continuous disease severity score that de-emphasizes waiting time could improve the allocation of cadaveric livers for transplantation. This report describes the development and initial implementation of this new plan. The goal was to develop a continuous disease severity scale that uses objective, readily available variables to predict mortality risk in patients with end-stage liver disease and reduce the emphasis on waiting time. Mechanisms were also developed for inclusion of good transplant candidates who do not have high risk of death but for whom transplantation may be urgent. The Model for End-Stage Liver Disease (MELD) and Pediatric End-Stage Liver Disease (PELD) scores were selected as the basis for the new allocation policy because of their high degree of accuracy for predicting death in patients having a variety of liver disease etiologies and across a broad spectrum of liver disease severity. Except for the most urgent patients, all patients will be ranked continuously under the new policy by their MELD/PELD score. Waiting time is used only to prioritize patients with identical MELD/PELD scores. Patients who are not well served by the MELD/PELD scores can be prioritized through a regionalized peer review system. This new liver allocation plan is based on more objective, verifiable measures of disease severity with minimal emphasis on waiting time. Application of such risk models provides an evidenced-based approach on which to base further refinements and improve the model.
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                Author and article information

                Contributors
                Journal
                World J Clin Cases
                WJCC
                World Journal of Clinical Cases
                Baishideng Publishing Group Inc
                2307-8960
                6 December 2018
                6 December 2018
                : 6
                : 15
                : 995-1006
                Affiliations
                Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410000, Hunan Province, China
                Department of Infectious Diseases, Xiangya Hospital, Central South University, Changsha 410000, Hunan Province, China
                Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410000, Hunan Province, China
                Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410000, Hunan Province, China
                Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410000, Hunan Province, China. tanhz99@ 123456qq.com
                Author notes

                Author contributions: Wu SL contributed to the study inception and design, literature search and selection, data acquisition, and analysis and writing of the manuscript; Zheng YX contributed to the study inception, literature selection, and data analysis and discussion; Tian ZW contributed to the literature search and selection, language editing, and manuscript revision; Chen MS contributed to the quality assessment and manuscript revision; Tan HZ contributed to the study design, manuscript revision, and study supervision; all authors approved the final version of the manuscript.

                Correspondence to: Hong-Zhuan Tan, PhD, Professor, Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, 110 Xiangya Road, Changsha 410000, Hunan Province, China. tanhz99@ 123456qq.com

                Telephone: +86-731-88858435 Fax: +86-731-84805454

                Article
                jWJCC.v6.i15.pg995
                10.12998/wjcc.v6.i15.995
                6288518
                30568954
                25f509e1-d541-41dc-b43c-85bfc8bfd4f2
                ©The Author(s) 2018. Published by Baishideng Publishing Group Inc. All rights reserved.

                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.

                History
                : 14 September 2018
                : 8 November 2018
                : 14 November 2018
                Categories
                Meta-Analysis

                liver cirrhosis,decompensated,mortality,accuracy,meta-analysis

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