Literature DB >> 34090805

A systematic review of prediction models for post-hepatectomy liver failure in patients undergoing liver surgery.

Kenji Yoshino1, Tomoaki Yoh2, Kojiro Taura3, Satoru Seo2, Ruben Ciria4, Javier Briceño-Delgado4.   

Abstract

BACKGROUND: The aim of this systematic review is to evaluate the current evidence in the context of clinical prediction model for post-hepatectomy liver failure (PHLF).
METHODS: A systematic search of the English literature for a period from December 2005 to September 2020 was conducted. Primary outcome was defined using the three common PHLF criteria (50-50 criteria, peak bilirubin>7 mg/dl criteria, and ≥ grade B PHLF criteria by the International Study Group of Liver Surgery). Studies that reported the value of area under receiver operative characteristic curve (AUC) for the occurrence of PHLF were included.
RESULTS: Twenty eight of 1327 screened articles were eligible for inclusion. Eighteen studies developed the prediction models. The median AUC was found to be 0.79 (0.65-0.933). The parameters related to the amount of future liver remnant volume were most commonly identified as significant predictors for PHLF in statistical analysis (24 studies) and were most frequently incorporated in the prediction models (18 studies). The parameters associated with portal hypertension were significant for predicting PHLF in 16 studies and were adopted in the prediction models in 14 studies.
CONCLUSION: Parameters related to future liver remnant volume and portal hypertension seem to be facilitating in predicting PHLF.
Copyright © 2021 International Hepato-Pancreato-Biliary Association Inc. Published by Elsevier Ltd. All rights reserved.

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Year:  2021        PMID: 34090805     DOI: 10.1016/j.hpb.2021.05.002

Source DB:  PubMed          Journal:  HPB (Oxford)        ISSN: 1365-182X            Impact factor:   3.647


  1 in total

1.  Early postoperative serum aspartate aminotransferase for prediction of post-hepatectomy liver failure.

Authors:  Watoo Vassanasiri; Narongsak Rungsakulkij; Wikran Suragul; Pongsatorn Tangtawee; Paramin Muangkaew; Somkit Mingphruedhi; Suraida Aeesoa
Journal:  Perioper Med (Lond)       Date:  2022-10-07
  1 in total

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