Acute biliary pancreatitis (ABP) is a potentially life-threatening condition caused by common bile duct (CBD) stones or sludge, which requires prompt diagnosis and treatment by endoscopic removal of the material. Accurate detection of CBD stones is warranted to select patients for early therapeutic endoscopic retrograde cholangiopancreatography (ERCP). In clinical practice the decision to perform an ERCP is often based on biochemical and radiological criteria despite they already have been shown to be unreliable predictors of CBD stone presence. Endoscopic ultrasound (EUS) is not currently a worldwide standard diagnostic procedure early in the course of acute biliary pancreatitis, but it has been shown to be accurate, safe and cost effective in diagnosing biliary obstructions compared with magnetic resonance cholangiopancreatography (MRCP) and ERCP and therefore in preventing unnecessary ERCP and its related complications. The investigators aim to investigate the clinical usefulness of early EUS in the management of ABP. All consecutive patients entering the emergency department due to acute abdominal pain and showing biochemical and/or radiological findings consistent with possible ABP will be prospectively enrolled. Patients will be classified as having a low, moderate, or high probability of CBD stones, according to established risk stratification. All enrolled patients will undergo EUS within 48 h of their admission. ERCP will be performed immediately after EUS only in those cases with proven CBD stones or sludge. The following parameters will be investigated: (1) clinical: age, sex, fever; (2) radiological: dilated CBD, (3) biochemical: bilirubin, aspartate aminotransferase (AST), alanine aminotransferase (ALT), gamma glutamyl transferase (gGT), alkaline phosphatase (ALP), amylase, lipases, C-reactive protein (CRP). Association between presence of CBD stone at EUS and the individual predictors were assessed by univariate logistic regression. Predictors significantly associated with CBD stones (p\<0.05) will enter in a multivariate logistic regression model.
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Reliability of early EUS
Timeframe: Twenty-four hours