Machine learning effectively predicts postpancreatectomy acute pancreatitis

A novel machine learning model successfully predicts postpancreatectomy acute pancreatitis (PPAP) in patients following pancreaticoduodenectomy. In a cohort of 381 patients, 88 (23.09%) developed PPAP, which was notably associated with a higher occurrence of postoperative pancreatic fistulas (55.68%). Various algorithms, including logistic regression and gradient boosting, were tested, with recursive feature elimination optimizing variable selection. This model aims to enhance proactive management strategies for clinicians dealing with this surgical complication.