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Patients with acute on chronic liver failure have a risk of developing multiorgan failure and a high mortality. The current scoring systems defining the outcome of patients with acute decompensation of cirrhosis fail to identify patients that progress to Acute-on-chronic liver failure (ACLF).
The aim of the study is to evaluate if one can identify these patients early on with the proposed biomarkers: dimethylarginines and ischemia modified albumin.
Patients with acute-on-chronic liver failure (ACLF) are at risk of multiorgan failure and high mortality. Recent data suggest that patients with decompensated liver cirrhosis have higher ADMA (asymmetrical dimethylarginine) levels compared to compensated cirrhosis and plasma ADMA levels correlate with severity of liver dysfunction and inflammation. There is also an increase in symmetric dimethylarginine (SDMA), a stereo-isomer of ADMA, which is largely excreted by the kidney. Plasma SDMA levels have been shown to be associated with patients
progressing to renal failure. In a pilot study by our group involving 52 patients with acute decompensation of chronic liver disease, we showed an increase in the summed product of ADMA and SDMA, which we termed dimethylarginine score ('DAS'): This was shown to have a good predictive utility for outcome in this small group of patients (AUROC=0.89).
Furthermore, we and others have shown that albumin of patients with advanced liver disease has widespread abnormalities. The amount of albumin that is found to have reduced metal binding capacity as a consequence of oxidative damage is termed Ischemia Modified Albumin (IMA).
Our data shows that patients with ACLF who die have a significantly increased IMA/serum albumin ratio (IMAR). The summation of these two pathologically relevant biomarkers (DAS+IMAR) we termed DASIMAR and found this score to have a better predictive utility than DAS alone (AUROC:0.91).
Primary objective : To identify the patients early on that progress to ACLF which would facilitate a goal directed therapeutic approach.
Secondary objective : Generation of this dataset will further define and enable prognostication of ACLF. If this study reveals a role for these biomarkers in patients with ACLF, commercial development of simple kits may be possible.
Observational Model: Cohort, Time Perspective: Prospective
University College London Hospital
University College London Hospitals
Published on BioPortfolio: 2014-08-27T03:15:48-0400
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