Applying Ockham's razor to pancreatitis prognostication: a four-variable predictive model

We sought to develop a simple yet accurate prognostic scoring system to determine the severity of acute pancreatitis at admission.

Because acute pancreatitis has a variable and frequently unpredictable course, identifying individuals at greatest risk for significant, life-threatening complications and stratifying their care appropriately remain a concern. Previous prognostic scoring systems predict severity reasonably well but are limited by time constraints, are unwieldy to use, or both.

Data from the international phase III trial of the platelet-activating factor receptor-antagonist Lexipafant were used to develop a 4-variable prognostic model. We then compared the model's ability to predict the severity of acute pancreatitis with the Ranson, Glasgow, and APACHE II systems.

The model (BALI), which included BUN >or=25 mg/dL, Age >or=65 years, LDH >or=300 IU/L, and IL-6 >or=300 pg/mL, measured at admission, was similar to the Ranson, Glasgow, and APACHE II systems in its ability to identify increased mortality from acute pancreatitis. The receiver operating characteristic curve area for the BALI model was >or=0.82 +/- 0.03 (mean +/- SD) versus 0.75 +/- 0.04 (Ranson), 0.80 +/- 0.03 (Glasgow), and 0.79 +/- 0.03 (APACHE II). Furthermore, at a prevalence of 15%, the positive and negative predictive values for increased mortality were similar for all systems.

The prognostic ability of the BALI 4-variable model was similar to the Ranson, Glasgow, and APACHE II systems but is unique in its simplicity and ability to accurately predict disease severity when used at admission or anytime during the first 48 hours of hospitalization.