[Analysis of short-term prognosis on patients with chronic severe hepatitis B using the model for end-stage liver disease]

Abstract

Objective: To study the practical clinical use of the model for end-stage liver disease (MELD) and assess its validity in predicting the short-term (3 mouths) prognosis of patients with chronic severe hepatitis B. The optimal cut-off values of MELD to discriminate between deceased and surviving patients were calculated by using receiver operator characteristic (ROC) curve.

Methods: The clinical information of 139 patients with chronic severe hepatitis B was collected. The patients were divided into two groups, including cirrhosis group and non-cirrhosis group (chronic hepatitis group). All the patients were evaluated with MELD. The death rate was recorded within 3 months.

Results: (1)The scores of MELD in all patients were higher than 20 points. The value of MELD between chronic hepatitis group [(31.34+/-7.00) scores, n=72] and cirrhosis group [(31.97+/-6.82) scores, n=67] had no significant difference(P>0.05). The mortality between the two groups had no significant difference, too. (2)The mortality within 3 months was 58.3% (81/139 cases). The mortality of the patients whose MELD score were 20-30 points, 30-40 points and higher than 40 points were 35.6% (26/73 cases), 76.6% (36/47 cases) and 100% (19/19 cases), respectively. Comparing with the higher scores the mortality was increased at the same MELD score. There were no significant difference in mortality between chronic severe hepatitis B and cirrhosis severe hepatitis B (all P>0.05). The optimal cut-off value of MELD score to predict the prognosis of patients was 31, with sensitivity and specificity were 64.2% and 91.4%, respectively, and c-statistic was 0.809 (95% CI 0.738-0.879).

Conclusion: The onset of chronic liver failure based on cirrhosis might have no important effect on the short-term prognosis. The MELD score can serve as an index of the severity of patients with chronic severe hepatitis B, and it can be used to predict accurately the short-term prognosis.