DOI: https://doi.org/10.36347/sjams.2026.v14i08.004

Pages: 1106-1111

Background: Early identification of severe acute pancreatitis (AP) in children is essential for appropriate risk stratification and timely management. Conventional biochemical markers have limited ability to predict disease severity. D-dimer, a fibrin degradation product reflecting activation of coagulation and fibrinolysis, has shown promising results as an early predictor of severe AP in adults; however, evidence in children remains limited. Objective: To determine the association between serum D-dimer level and the severity of acute pancreatitis in children. Materials and Methods: This cross-sectional observational study was conducted in the Department of Pediatric Gastroenterology and Nutrition, Bangabandhu Sheikh Mujib Medical University (BSMMU), Dhaka, Bangladesh, from March 2021 to June 2022. Twenty children diagnosed with acute pancreatitis according to the International Study Group of Pediatric Pancreatitis: In Search for a Cure (INSPPIRE) criteria were enrolled consecutively. Serum D-dimer was measured on the day of admission. Patients were classified into mild and severe acute pancreatitis using the Pediatric Acute Pancreatitis Severity Score (PAPS). Receiver operating characteristic (ROC) curve analysis was performed to determine the optimal cutoff value, and the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy of serum D-dimer were calculated. Results: Severe acute pancreatitis was identified in 30.0% of patients, while 70.0% had mild disease. The mean serum D-dimer level was significantly higher in children with severe acute pancreatitis than in those with mild disease (3.89 ± 3.39 vs. 1.28 ± 1.60 µg/mL; p<0.001). ROC curve analysis demonstrated good diagnostic performance of serum D-dimer for predicting severe acute pancreatitis. At the optimal cutoff value (>1.66 µg/mL), serum D-dimer showed satisfactory sensitivity, specificity, PPV, NPV, and overall diagnostic accuracy for identifyi