[Prediction of perioperative mortality in patients with advanced liver disease and abdominal surgery by the use of different scoring systems and tests]

Z Gastroenterol. 2008 Nov;46(11):1283-9. doi: 10.1055/s-2008-1027624. Epub 2008 Nov 14.
[Article in German]

Abstract

Patients with advanced liver disease show increased morbidity and mortality after hepatic resection and non-hepatic digestive surgery. Furthermore, postoperative liver failure is associated with a poor outcome, representing an important clinical problem. For evaluation of the perioperative mortality and the hepatic function, several scoring systems, clinical parameters, and static and dynamic tests are available. Recently, the Model for End-Stage Liver Disease (MELD) has been shown to provide a complementary predictive value to the widely used Child Turcotte Pugh score. Patients with Child Turcotte Pugh class C cirrhosis and MELD scores >14 are generally not considered for surgical intervention. Patients with Child Turcotte Pugh class B cirrhosis and MELD scores >8-14 have an increased perioperative risk and the indication for surgery should be assessed carefully. In patients with Child Turcotte Pugh class A cirrhosis and MELD scores of <or= 8, perioperative mortality is low. Although not routinely used, dynamic tests can provide additional information on the expected residual hepatic function in patients with Child Turcotte Pugh class A cirrhosis and MELD scores of <or= 8 in whom hepatic resection is needed. Besides other dynamic tests, the indocyanine green (ICG) clearance and the monoethylglycinxylid (MEGX) clearance tests have been satisfactorily evaluated.

Publication types

  • English Abstract
  • Review

MeSH terms

  • Abdomen / surgery*
  • Hospital Mortality
  • Humans
  • Liver Cirrhosis / classification
  • Liver Cirrhosis / mortality*
  • Liver Failure / classification
  • Liver Failure / mortality*
  • Liver Function Tests / methods*
  • Postoperative Complications / mortality*
  • Prognosis
  • Risk Assessment / statistics & numerical data