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World J Gastrointest Surg. Dec 27, 2012; 4(12): 281-283
Published online Dec 27, 2012. doi: 10.4240/wjgs.v4.i12.281
Incorporating dynamics for predicting poor outcome in acute liver failure patients
Robert AFM Chamuleau, Kama A Wlodzimirow, Ameen Abu-Hanna
Robert AFM Chamuleau, Tytgat Institute for Liver and Intestinal Research, Academic Medical Center, University of Amsterdam, 1105 BK Amsterdam, The Netherlands
Kama A Wlodzimirow, Ameen Abu-Hanna, Department of Medical Informatics, Academic Medical Center, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands
Author contributions: Wlodzimirow KA collected the materials; Chamuleau RAFM and Wlodzimirow KA wrote the manuscript; Abu-Hanna A revised the manuscript critically; all authors approved the final version of the manuscript.
Correspondence to: Robert AFM Chamuleau, MD, PhD, Tytgat Institute for Liver and Intestinal Research, Academic Medical Center, University of Amsterdam, Meibergdreef 69-71, 1105 BK Amsterdam, The Netherlands.
Telephone: +31-205-668832 Fax: +31-205-669190
Received: July 6, 2012
Revised: October 29, 2012
Accepted: December 20, 2012
Published online: December 27, 2012

Acute liver failure (ALF), also known as fulminant hepatic failure (FHF), is a devastating clinical syndrome with a high mortality of 60%-90%. An early and exact assessment of the severity of ALF together with prediction of its further development is critical in order to determine the further management of the patient. A number of prognostic models have been used for outcome prediction in ALF patients but they are mostly based on the variables measured at one time point, mostly at admission. ALF patients rarely show a static state: rapid progress to a life threatening situation occurs in many patients. Since ALF is a dynamic process, admission values of prognostic variables change over time during the clinical course of the patient. Kumar et al developed a prognostic model [ALF early dynamic (ALFED)] based on early changes in values of variables which predicted outcome. ALFED is a model which seems to be worthwhile to test in ALF patients in other parts of the world with different aetiologies. Since the exact pathophysiology of ALF is not fully known and is certainly complex, we believe that adding promising variables involved in the pathophysiology of ALF to the dynamic approach might even further improve prognostic performance. We agree with Kumar et al that an improved dynamic prognostic model should be based on simplicity (easily to be performed at the bedside) and accuracy. Our comments presented in this paper may be considered as recommendations for future optimization of ALF prediction models.

Keywords: Acute liver failure, Fulminant hepatic failure, Prediction models, Prognosis, Prediction