title: Prospective derivation and validation of early dynamic model for predicting outcome in patients with acute liver failure.
abstract: OBJECTIVE
  It is difficult to predict the outcome in patients with acute liver failure (ALF) using existing prognostic models. This study investigated whether early changes in the levels of dynamic variables can predict outcome better than models based on static baseline variables.
  
  
  METHODS
  380 patients with ALF (derivation cohort n=244, validation cohort n=136) participated in a prospective observational study. The derivation cohort was used to identify predictors of mortality. The ALF early dynamic (ALFED) model was constructed based on whether the levels of predictive variables remained persistently high or increased over 3 days above the discriminatory cut-off values identified in this study. The model had four variables: arterial ammonia, serum bilirubin, international normalised ratio and hepatic encephalopathy >grade II. The model was validated in a cohort of 136 patients with ALF.
  
  
  RESULTS
  The ALFED model demonstrated excellent discrimination with an area under the receiver operator characteristic curve of 0.91 in the derivation cohort and of 0.92 in the validation cohort. The model was well calibrated in both cohorts and showed a similar increase in mortality with increasing risk scores from 0 to 6. The performance of the ALFED model was superior to the King's College Hospital criteria and the Model for End stage Liver Disease score, even when their 3-day serial values were taken into consideration. An ALFED score of ≥4 had a high positive predictive value (85%) and negative predictive value (87%) in the validation cohort.
  
  
  CONCLUSIONS
  The ALFED model accurately predicted outcome in patients with ALF, which may be useful in clinical decision-making.
authors.affiliation: Department of Gastroenterology, All India Institute of Medical Sciences, New Delhi, India.
authors.forename: Ramesh
authors.initials: R
authors.lastname: Kumar
authors.lastname: Shalimar
authors.forename: Hanish
authors.initials: H
authors.lastname: Sharma
authors.forename: Rohit
authors.initials: R
authors.lastname: Goyal
authors.forename: Ajay
authors.initials: A
authors.lastname: Kumar
authors.forename: Shankar
authors.initials: S
authors.lastname: Khanal
authors.forename: Shyam
authors.initials: S
authors.lastname: Prakash
authors.forename: S Datta
authors.initials: SD
authors.lastname: Gupta
authors.forename: Subrat Kumar
authors.initials: SK
authors.lastname: Panda
authors.forename: Subrat Kumar
authors.initials: SK
authors.lastname: Acharya
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000641:Ammonia / Q000097:blood*; D000704:Analysis of Variance; D005260:Female; D006801:Humans; D017114:Liver Failure, Acute / Q000097:blood / Q000401:mortality*; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D011379:Prognosis; D011446:Prospective Studies; D015203:Reproducibility of Results; D012720:Severity of Illness Index; D055815:Young Adult
chemical_list: D000641:Ammonia