为在尖锐的肝失败病人预言差的结果合并动力学

查看全文 作　　者：Robert AFM Chamuleau;Kama A Wlodzimirow;Ameen Abu-Hanna

机构地区：Tytgat Institute for Liver and Intestinal Research, Academic Medical Center, University of Amsterdam, 1105 BK Amsterdam, The Netherlands;Department of Medical Informatics, Academic Medical Center, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands

出　　处：《World Journal of Gastrointestinal Surgery》索引2012年第4卷第12期,共3页

摘　　要：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. 关键词：ACUTE liver FAILURE FULMINANT HEPATIC FAILURE PREDICTION models PROGNOSIS PREDICTION

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为在尖锐的肝失败病人预言差的结果合并动力学

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