Abstract
Background: Acute pancreatitis is a common condition with a variable prognosis. While the overall mortality rate of acute pancreatitis is relatively low, ranging between 3 and 5% in most cases, severe forms can result in significantly higher morbidity and mortality. Therefore, early risk assessment is crucial for optimizing management and treatment. The aim of the present study wasto compare simple prognostic markers and identify the best predictors of severity in patients with acute pancreatitis. Material and Methods: A retrospective analysis was carried outon 108 patients admitted in our center during one year with acute biliary pancreatitis. Acute pancreatitis severity was stratified based on the revised Atlanta criteria. Results: 108 subjects (mean age of 60.1 ± 18.6, 65.7% females) diagnosed with acute biliary pancreatitis were included. Based on the Atlanta criteria, 59.3% (64/108) of the subjects were classified as having mild acute biliary pancreatitis, 35.2% (38/108) as having a moderate-severe pancreatitis, and 5.5% (6/108) were classified as having severe acute pancreatitis. In univariate analysis, the following parameterswere associatedwith at least a moderate-severe form of acute pancreatitis: Balthazar score, fasting blood glucose (mg/dL), modified CTSI score, CRP values at 48 h, BISAP score at admission, CTSI score, Ranson score, duration of hospitalization (days), and the presence of leukocytosis (×1000/µL) (all p < 0.05).BISAP score at admission (AUC-0.91), CRP levels at 48 h (AUC-0.92), mCTSI (AUC-0.94), and CTSI score (AUC-0.93) had the highest area under the curve (AUC) for predicting the severity of acute pancreatitis. In multivariate analysis, the model including the following independent parameters was predictive for the severity of acute pancreatitis: CTSI score (p < 0.0001), BISAP score (p = 0.0082), and CRP levels at 48 h (p = 0.0091), respectively. The model showed a slightly higher AUC compared to the independent predictors (AUC-0.96). Conclusions: The use of a multiparametric prediction model can increase the accuracy of predicting severity in patients with acute biliary pancreatitis.