{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,2]],"date-time":"2026-10-02T16:45:28Z","timestamp":1790959528533,"version":"4.1.0"},"reference-count":33,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2024,3,25]],"date-time":"2024-03-25T00:00:00Z","timestamp":1711324800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["DEN Open"],"published-print":{"date-parts":[[2024,4]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Pancreatitis following endoscopic retrograde cholangiopancreatography (ERCP) can lead to significant morbidity and mortality. We aimed to develop an accurate post\u2010ERCP pancreatitis risk prediction model using easily obtainable variables.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Using prospective multi\u2010center ERCP data, we performed logistic regression using stepwise selection on several patient\u2010, procedure\u2010, and endoscopist\u2010related factors that were determined a priori. The final model was based on a combination of the Bayesian information criterion and Akaike's information criterion performance, balancing the inclusion of clinically relevant variables and model parsimony. All available data were used for model development, with subsequent internal validation performed on bootstrapped data using 10\u2010fold cross\u2010validation.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Data from 3021 ERCPs were used to inform models. There were 151 cases of post\u2010ERCP pancreatitis (5.0% incidence). Variables included in the final model included female sex, pancreatic duct cannulation, native papilla status, pre\u2010cut sphincterotomy, increasing cannulation time, presence of biliary stricture, patient age, and placement of a pancreatic duct stent. The final model was discriminating, with a receiver operating characteristic curve statistic of 0.79, and well\u2010calibrated, with a predicted risk\u2010to\u2010observed risk ratio of 1.003.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>We successfully developed and internally validated a promising post\u2010ERCP pancreatitis clinical prediction model using easily obtainable variables that are known at baseline or observed during the ERCP procedure. The model achieved an area under the curve of 0.79. External validation is planned as additional data becomes available.<\/jats:p><\/jats:sec>","DOI":"10.1002\/deo2.355","type":"journal-article","created":{"date-parts":[[2024,3,25]],"date-time":"2024-03-25T11:34:45Z","timestamp":1711366485000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Development and validation of a practical clinical risk prediction model for post\u2010endoscopic retrograde cholangiopancreatography pancreatitis"],"prefix":"10.1002","volume":"4","author":[{"given":"Zhao Wu","family":"Meng","sequence":"first","affiliation":[{"name":"Department of Community Health Sciences University of Calgary  Calgary Canada"},{"name":"Department of Medicine Division of Gastroenterology and Hepatology University of Calgary  Calgary Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yibing","family":"Ruan","sequence":"additional","affiliation":[{"name":"Department of Oncology Cumming 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