Predicting 6-week mortality after acute variceal bleeding: role of Classification and Regression Tree analysis.

BACKGROUND

Available prognostic scores for mortality after acute variceal bleeding are mainly based on logistic regression analysis but may have some limitations that can restrict their clinical value.

AIMS: To assess the efficacy of a novel prognostic approach based on Classification and Regression Tree -CART- analysis to common easy-to-use models (MELD and Child-Pugh) for predicting 6-week mortality in patients with variceal bleeding.

METHODS

Sixty consecutive cirrhotic patients with acute variceal bleeding. CART analysis, MELD and Child-Pugh scores were performed to assess 6-week mortality. Receiver operating characteristic (ROC) curves were constructed to evaluate the predictive performance of the models.

RESULTS

Six-week rebleeding and mortality were 30% and 22%, respectively. Child-Pugh and MELD scores were clinically relevant for predicting 6 weeks mortality. CART analysis provided a simple algorithm based on just three bedside-available variables (albumin, bilirubin and in-hospital rebleeding), allowing accurate discrimination of two distinct prognostic subgroups with 3% and 80% mortality rates. All MELD, Child-Pugh and CART models showed excellent and comparable predictive accuracy, with areas under the ROC curves (AUROC) of 0.88, 0.84 and 0.91, respectively.

CONCLUSIONS

A simple CART algorithm combining albumin, bilirubin and in-hospital rebleeding allows an accurate predictive assessment of 6-week mortality after acute variceal bleeding.