Elsevier

Clinics in Liver Disease

Volume 20, Issue 3, August 2016, Pages 491-497
Clinics in Liver Disease

Prognosis and Prognostic Scoring Models for Alcoholic Liver Disease and Acute Alcoholic Hepatitis

https://doi.org/10.1016/j.cld.2016.02.007Get rights and content

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Key points

  • A discriminant function greater than or equal to 32 denotes increased mortality at 30 and 90 days.

  • Acute alcoholic hepatitis prognostic scores perform better at predicting patients likely to achieve short-term survival rather than those at high risk of death.

  • Combining prognostic factors may improve the ability to identify patients at high risk of death and nonresponders to medical therapy.

Modified discriminant function or Maddrey score

The realization that biochemical parameters reflecting liver injury and synthetic function can predict short-term mortality based on experience with early clinical trials led to the development of the original discriminant function (DF), which was later slightly modified and remains extensively used today.2, 3 The formula is as follows:4.6 × [Protime patient – control (in seconds)] + total bilirubin (mg/dL)

Perhaps the most valuable information provided by DF is its ability to predict 28-day

Glasgow alcoholic hepatitis score

Glasgow alcoholic hepatitis score (GAHS) is a more recent attempt to provide a dynamic assessment of mortality risk and prognosis using readily available biochemical parameters and their evolution over time.9 GAHS is derived from the following variables: age, Day 1 serum bilirubin, Day 1 blood urea, Day 6 to 9 serum bilirubin, prothrombin time, and peripheral blood white blood cell count (Table 2).

GAHS scores range from 5 to 12. For patients with a GAHS greater than or equal to 9, the 28-day

Age, serum bilirubin, international normalized ratio and creatinine score

ABIC is an acronym for Age, serum Bilirubin, International normalized ratio (INR), and Creatinine.13 The formula was derived from a cohort of patients with biopsy-proven AAH then validated and is as follows:(Age × 0.1) + (total bilirubin (mg/dL) × 0.08) + (serum creatinine (mg/dL) × 0.3) + (INR × 0.8)

ABIC cutoff values of less than or equal to 6.71, 6.71 to 9, and greater than 9.0 categorize patients into low, intermediate, and high risk of 90-day death (100%, 70%, and 25% of survival,

Lille score

The paucity of effective therapies for AAH and the need for early identification of patients with severe AH (defined as DF ≥32) not responding to corticosteroids led to the development of the Lille score.16 Six reproducible variables (age, renal insufficiency, albumin, prothrombin time, bilirubin, and evolution of bilirubin at Day 7) were incorporated into the model. A Lille score calculator is available online (http://www.lillemodel.com/score.asp), which aids with the generation of a score

Model for end-stage liver disease

Since its development as a prognostic tool for mortality from transjugular intrahepatic portosystemic hunting, model for end-stage liver disease (MELD) has become the most widely used scoring system in the setting of advanced liver disease with applications ranging from assigning liver transplant organ allocation priority to assessing the risk of morbidity and mortality from surgery in patients with cirrhosis.23, 24, 25 As a robust predictor of mortality from liver disease, it is not surprising

Combining prognostic models

The currently used models for predicting AH prognosis each have benefits and disadvantages. Louvet and colleagues7 performed a study in 2015 looking at the utility of combining prognostic models to improve outcome prediction. They compared DF + Lille versus MELD + Lille versus ABIC + Lille. Looking at 2- and 6-month mortality rates, they found that MELD + Lille model was the best at predicting mortality in patients with severe AH.

Summary

The DF remains the most widely used prognostic score in clinical practice for AH and DF greater than or equal to 32 has remained largely synonymous with severe disease. Most clinical trials continue to use this as the main entry criterion to identify patients who are at risk of death and may benefit from pharmacologic or other interventions. The ability to identify patients at high risk of death may be improved by combining results from static and dynamic scoring systems for liver disease

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  • Cited by (0)

    The author has nothing to disclose.

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