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Malondialdehyde as a Prognostic Factor in Alcoholic Hepatitis
Onán Pérez-Hernández1, Emilio González-Reimers1, Geraldine Quintero-Platt1
1Servicio de Medicina Interna, Hospital Universitario de Canarias,Universidad de La Laguna, Tenerife, Canary Islands, Spain.
Alcohol and Alcoholism (Oxford, Oxfordshire)
|December 24, 2016
Summary
Malondialdehyde (MDA) levels offer superior short-term prognostic accuracy for severe alcoholic hepatitis compared to traditional scoring systems. Assessing MDA at admission and after one week can improve patient outcome prediction in this critical condition.
Area of Science:
- Hepatology
- Internal Medicine
- Biochemistry
Background:
- Alcoholic hepatitis is a severe liver disease with high mortality.
- Current prognostic scores for alcoholic hepatitis lack markers for oxidative stress.
- Lipid peroxidation, indicated by malondialdehyde (MDA), is implicated in alcoholic hepatitis pathogenesis.
Purpose of the Study:
- To evaluate the short-term prognostic value of malondialdehyde (MDA) and cytokines in severe alcoholic hepatitis.
- To compare the accuracy of MDA and established prognostic scores in predicting mortality.
Main Methods:
- Sixty-two patients with severe alcoholic hepatitis (Maddrey index >32) were studied.
- Prognostic scores (Maddrey, MELD, ABIC, Lille, Glasgow, MELD-Na, Child-Pugh) were calculated.
- Serum MDA and cytokine levels (IL-6, IL-8, IL-4, TNF-α, IFN-γ) were measured at admission and after 1 week.
Main Results:
- Twenty-four out of sixty-two patients died during the follow-up period.
- Malondialdehyde (MDA) demonstrated superior prognostic accuracy compared to all tested scores.
- MDA's predictive value was significant both at admission and after one week of treatment.
Conclusions:
- Malondialdehyde (MDA) assessment should be incorporated into the prognostic evaluation of alcoholic hepatitis.
- MDA levels provide valuable insights into short-term outcomes for patients with severe alcoholic hepatitis.
- Oxidative stress markers like MDA are crucial for improving patient management and predicting prognosis.

