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Prospective derivation and validation of early dynamic model for predicting outcome in patients with acute liver failure
  1. Ramesh Kumar1,
  2. Shalimar1,
  3. Hanish Sharma1,
  4. Rohit Goyal1,
  5. Ajay Kumar1,
  6. Shankar Khanal2,
  7. Shyam Prakash1,
  8. S Datta Gupta3,
  9. Subrat Kumar Panda3,
  10. Subrat Kumar Acharya1
  1. 1Department of Gastroenterology, All India Institute of Medical Sciences, New Delhi, India
  2. 2Department of Biostatistics, All India Institute of Medical Sciences, New Delhi, India
  3. 3Department of Pathology, All India Institute of Medical Sciences, New Delhi, India
  1. Correspondence to Dr Subrat K Acharya, Department of Gastroenterology and Human Nutrition, All India Institute of Medical Sciences, Room No.3105, 3rd Floor, Teaching Block, All India Institute of Medical Sciences, New Delhi 110029, India; subratacharya2004{at}yahoo.com

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.

Design 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.

Conclusion The ALFED model accurately predicted outcome in patients with ALF, which may be useful in clinical decision-making.

  • ALF
  • prognosis
  • India
  • acute fatty liver
  • acute liver failure
  • gastrointestinal pathology
  • hepatic encephalopathy
  • hepatitis
  • liver failure
  • liver
  • liver cirrhosis
  • cancer
  • hepatitis E
  • Helicobacter pylori
  • acid-related diseases
  • non-ulcer dyspepsia
  • genetic polymorphisms
  • gastric neoplasia

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Footnotes

  • Funding Supported by the Indian Council of Medical Research (ICMR) through the project “Advanced Center for Liver Diseases” to the Department of Gastroenterology, All India Institute of Medical Sciences, New Delhi.

  • Competing interests None.

  • Ethics approval Ethics approval was approved by the ethics committee of All India Institute of Medical Sciences.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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