Acute liver failure in Budd–Chiari syndrome and a model to predict mortality

Acute liver failure (ALF) occurs in approximately 1–2% of patients with Budd–Chiari syndrome (BCS). The primary objective of our study was to study the outcome of patients with BCS-ALF using the National Inpatient Sample (NIS) database and develop a mortality prediction model.

We identified all adult patients with BCS, with and without ALF, using ICD-9 or ICD-10. Using clinical variables, we identified risk factors for in-hospital mortality and developed a prediction model using logistic regression analysis. The model was built and validated in a training and validation datasets.

Between 2008 and 2017, of the estimated total of 5,306 (weighted sample size 26,110) BCS discharges, 325 (6.1%) patients (weighted sample size 1,598) presented with ALF. Of 325 BCS-ALF patients, 114 (34.7%, weighted n = 554) died and in contrast only 267 of 4,981 (5%, weighted n = 1310) without ALF died during the hospitalization. The independent risk factors that predicted mortality were age 50 years or older, acute respiratory failure, spontaneous bacterial peritonitis, sepsis and cancers. The prediction model that incorporated these risk factors had an area under the receiver operating characteristic curve (AUROC) of 0.85 (95% CI 0.80–0.90) for training data and 0.80 (95% CI 0.71–0.89) for validation data. The predicted mortality risk with low (score < 6), intermediate (score 6–16), and high risk (score ≥ 17) scores were 8%, 37% and 71%, respectively.

ALF due to BCS is associated with a very high in-hospital mortality that could be predicted with reasonable accuracy.