Published online Sep 21, 2023. doi: 10.3748/wjg.v29.i35.5138
Peer-review started: June 28, 2023
First decision: July 23, 2023
Revised: August 6, 2023
Accepted: August 28, 2023
Article in press: August 28, 2023
Published online: September 21, 2023
Biliary microlithiasis/sludge is detected in approximately 30% of patients with idiopathic acute pancreatitis (IAP). As recurrent biliary pancreatitis can be pre
To develop a machine learning (ML) based decision tool for the use of endosonography (EUS) in pancreatitis patients to detect sludge and microlithiasis.
We retrospectively used routinely recorded clinical and laboratory parameters of 218 consecutive patients with confirmed AP admitted to our tertiary care hospital between 2015 and 2020. Patients who did not receive EUS as part of the diagnostic work-up and whose pancreatitis episode could be adequately explained by other causes than biliary sludge and microlithiasis were excluded. We trained super
Twenty-eight categorized patients’ variables recorded at admission were identified to compute the predictor model with an accuracy of 0.84 [95% confidence interval (CI): 0.791-0.9185], positive predictive value of 0.84, and negative predictive value of 0.80 in the identification cohort (218 patients). In the validation cohort, the robustness of the prediction model was confirmed with an accuracy of 0.76 (95%CI: 0.673-0.8347), positive predictive value of 0.76, and negative predictive value of 0.78 (117 patients).
We present a robust and validated ML-based predictor model consisting of routinely recorded parameters at admission that can predict biliary sludge and microlithiasis as the cause of AP.
Core Tip: Occult biliary lithiasis represents the largest monocausally treatable aetiology group within idiopathic acute pancreatitis cases. The identification of this subgroup protects patients from pancreatitis recurrences and over- or underdiagnosis. Based on 28 easy-to-collect and widely available patient variables, a machine learning-based prediction score can be used to predict the presence or absence of biliary sludge or microlithiasis in the context of pancreatitis hospitalisation. We provide a web-based prediction tool to select patients for endosonography to investigate microlithiasis or sludge as the cause of pan