biostudies-literatureMao YXianyang Science and Technology Planning Projecte0332378https://www.ebi.ac.uk/biostudies/studies/S-EPMC12435719biostudies-literatureUnknown20(9)<h4>Background</h4>Post-endoscopic retrograde cholangiopancreatography pancreatitis (PEP) is the most common and clinically significant complication of ERCP, with an incidence of 3.5-9.7% in general populations and up to 14.7% in high-risk groups, leading to considerable morbidity, mortality, and healthcare costs. Although numerous multivariable prediction models have been developed, their predictor sets, methodological rigor, and clinical applicability remain highly variable.<h4>Method</h4>We conducted a PRISMA 2020-compliant systematic review and meta-analysis, prospectively registered in PROSPERO (CRD42024556967). Nine databases were searched to June 1, 2024, for studies developing or validating multivariable PEP risk prediction models. Data on study/model characteristics, predictors, aPloS oneRisk prediction model for post-endoscopic retrograde cholangiopancreatography pancreatitis: A systematic review and meta-analysis.PMC12435719L2023-ZDYF-SF-055Fan HOuyang XDong HHe WLi ELiu QWang XZhang CMao YQiu LfalseRisk prediction model for post-endoscopic retrograde cholangiopancreatography pancreatitis: A systematic review and meta-analysis.<h4>Background</h4>Post-endoscopic retrograde cholangiopancreatography pancreatitis (PEP) is the most common and clinically significant complication of ERCP, with an incidence of 3.5-9.7% in general populations and up to 14.7% in high-risk groups, leading to considerable morbidity, mortality, and healthcare costs. Although numerous multivariable prediction models have been developed, their predictor sets, methodological rigor, and clinical applicability remain highly variable.<h4>Method</h4>We conducted a PRISMA 2020-compliant systematic review and meta-analysis, prospectively registered in PROSPERO (CRD42024556967). Nine databases were searched to June 1, 2024, for studies developing or validating multivariable PEP risk prediction models. Data on study/model characteristics, predictors, a2025-01-01T00:00:00Z20252026-06-01T14:06:31.11Z2026-04-08T13:19:08.419ZS-EPMC124357194095303610.1371/journal.pone.0332378