RESUMO
BACKGROUND: Early risk stratification of acute pancreatitis is crucial to improve clinical outcomes. The objective of this study was to evaluate the ability of pancreatic stone protein (PSP) to predict acute pancreatitis severity and to compare it with the biomarkers and severity scores currently used for that purpose. PATIENTS AND METHODS: Prospective single-center observational study enrolling 268 adult patients with acute pancreatitis. Biomarkers including PSP were measured upon admission to the Emergency Department and severity scores as SOFA, PANC-3, and BISAP were computed. Patients were classified into mild-moderate (non-severe) and severe acute pancreatitis according to the Determinant-Based Classification Criteria. Area under the curve (AUC) and regression analysis were used to analyze the discrimination abilities and the association of biomarkers and scores with severity. RESULTS: Two hundred and thirty-five patients (87.7%) were classified as non-severe and 33 (12.3%) as severe acute pancreatitis. Median [IQR] PSP was increased in patients with severe acute pancreatitis (890 µg/L [559-1142] vs. 279 µg/L [141-496]; p < 0.001) and it was the best predictor (ROC AUC: 0.827). In multivariate analysis, PSP and urea were the only independent predictors for severe acute pancreatitis and a model combining them both ("biomarker model") showed an AUC of 0.841 for prediction of severe acute pancreatitis, higher than the other severity scores. CONCLUSIONS: PSP is a promising biomarker for predicting the severity of acute pancreatitis upon admission. A model combining PSP and urea might further constitute a potential tool for early risk stratification of this disease.