title: Identification of patients with decompensated cirrhosis at high risk for death: improving the prediction by hepatic venous pressure gradient?
abstract: OBJECTIVE
  The incremental usefulness of adding hepatic venous pressure gradient (HVPG) for predicting the risk of death has not, to our knowledge, been evaluated among patients with decompensated cirrhosis. We investigated whether the incorporation of the HVPG in an established model improved the prediction of death in a cohort of decompensated cirrhosis patients.
  
  
  METHODS
  We used data from 106 consecutive patients with decompensated cirrhosis who underwent a hemodynamic study between January 2006 and December 2007, to investigate whether the HVPG improved the risk discrimination of a patient beyond an assessment that was based on the Model for End-stage Liver Disease (MELD) or MELD-Na. We used occurrence vs. non-occurrence of events within 12 months as the outcome for analysis.
  
  
  RESULTS
  For prediction of 12 months survival, the area under the receiver-operating characteristic curve (AUROC) for the MELD-Na was significantly greater than that of the MELD (79.4% vs. 70.5%, p=0.05). The MELD performed similar to the HVPG (70.5% vs. 71.2%, p=0.471). Adding the HVPG measurement to the MELD or the MELD-Na did not result in significant increase of the AUROC,with only a small improvement of about 5% in both cases.
  
  
  CONCLUSIONS
  The MELD-Na is the most predictive for 12-month survival in patients with decompensated cirrhosis. The addition of the HVPG to the MELD or the MELD-Na score does not appear to improve the prognostic accuracy of the MELD or the MELD-Na score significantly.
authors.affiliation: Department of Internal Medicine, Inje University College of Medicine, Busan, Korea.
authors.forename: Seung Ha
authors.initials: SH
authors.lastname: Park
authors.forename: Ha Young
authors.initials: HY
authors.lastname: Park
authors.forename: Jong Woo
authors.initials: JW
authors.lastname: Kang
authors.forename: Jin Se
authors.initials: JS
authors.lastname: Park
authors.forename: Kyong Jin
authors.initials: KJ
authors.lastname: Shin
authors.forename: Chang Hoon
authors.initials: CH
authors.lastname: Kim
authors.forename: Ki Tae
authors.initials: KT
authors.lastname: Suk
authors.forename: Gwang Ho
authors.initials: GH
authors.lastname: Baik
authors.forename: Jin Bong
authors.initials: JB
authors.lastname: Kim
authors.forename: Dong Joon
authors.initials: DJ
authors.lastname: Kim
authors.forename: Heon Young
authors.initials: HY
authors.lastname: Lee
mesh_terms: D000328:Adult; D000368:Aged; D015415:Biomarkers / Q000097:blood; D001795:Blood Pressure Determination; D003661:Decision Support Techniques; D016002:Discriminant Analysis; D005260:Female; D006503:Hepatic Veins / Q000503:physiopathology*; D006801:Humans; D008103:Liver Cirrhosis / Q000097:blood / Q000150:complications / Q000175:diagnosis* / Q000401:mortality* / Q000503:physiopathology; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D011237:Predictive Value of Tests; D011379:Prognosis; D012372:ROC Curve; D012189:Retrospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D012964:Sodium / Q000097:blood; D016019:Survival Analysis; D013997:Time Factors; D014690:Venous Pressure
chemical_list: D015415:Biomarkers; D012964:Sodium