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Prediction for post-ERCP pancreatitis in non-elderly patients with common bile duct stones: a cross-sectional study at a major Chinese tertiary hospital (2015–2023)
- Source :
- BMC Medical Informatics and Decision Making, Vol 24, Iss 1, Pp 1-11 (2024)
- Publication Year :
- 2024
- Publisher :
- BMC, 2024.
-
Abstract
- Abstract Background Post-ERCP pancreatitis is one of the most common adverse events in ERCP-related procedures. The purpose of this study is to construct an online model to predict the risk of post-ERCP pancreatitis in non-elderly patients with common bile duct stones through screening of relevant clinical parameters. Methods A total of 919 cases were selected from 7154 cases from a major Chinese tertiary hospital. Multivariable logistic regression model was fitted using the variables selected by the LASSO regression from 28 potential predictor variables. The internal and external validation was assessed by evaluating the receiver operating characteristic curve and the area under curve. Restricted cubic spline modelling was used to explore non-linear associations. The interactive Web application developed for risk prediction was built using the R “shiny” package. Results The incidence of post-ERCP pancreatitis was 5.22% (48/919) and significantly higher in non-elderly patients with female, high blood pressure, the history of pancreatitis, difficult intubation, endoscopic sphincterotomy, lower alkaline phosphatase and smaller diameter of common bile duct. The predictive performance in the test and external validation set was 0.915 (95% CI, 0.858–0.972) and 0.838 (95% CI, 0.689–0.986), respectively. The multivariate restricted cubic spline results showed that the incidence of pancreatitis was increased at 33–50 years old, neutrophil percentage > 58.90%, hemoglobin > 131 g/L, platelet 241.40 × 109/L, total bilirubin > 18.39 umol / L, aspartate amino transferase
Details
- Language :
- English
- ISSN :
- 14726947
- Volume :
- 24
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- BMC Medical Informatics and Decision Making
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.93ccdead4c4239a1d0a51b121553f7
- Document Type :
- article
- Full Text :
- https://doi.org/10.1186/s12911-024-02541-z