| ISSN |
1007-9327 (print) and 2219-2840 (online) |
| Open Access |
This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/ |
| Copyright |
© The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved. |
| Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
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| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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| Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
| Website |
http://www.wjgnet.com |
| Category |
Gastroenterology & Hepatology |
| Manuscript Type |
Retrospective Study |
| Article Title |
Risk prediction of biliary infection after endoscopic drainage for malignant perihilar biliary obstruction: A 10-year multicenter retrospective study
|
| Manuscript Source |
Invited Manuscript |
| All Author List |
Yi-Fei Wang, Ke Han, Na An, Ya-Nan Sun, Feng Gao, Yong Sun, Di Zhang, Zhi-Feng Zhao, Qing Guo, Jiang-Ning Gu and Zhuo Yang |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Zhuo Yang, Chief Physician, MD, Professor, Department of Endoscopy, General Hospital of Northern Theater Command, No. 83 Wenhua Road, Shenhe District, Shenyang 110016, Liaoning Province, China. yangzhuocy@163.com |
| Key Words |
Malignant perihilar biliary obstruction; Endoscopic retrograde cholangiopancreatography; Postoperative biliary infection; Risk factors; Artificial neural network |
| Core Tip |
This study established logistic regression and artificial neural network (ANN) models to preoperatively predict postoperative biliary infection-a serious complication worsening surgical outcomes and short-term prognosis in patients with malignant perihilar biliary obstruction undergoing endoscopic retrograde cholangiopancreatography drainage. Multivariate logistic regression identified key preoperative risk factors, notably hypokalemia, Bismuth-Corlett classification, and elevated aspartate transaminase levels. The ANN model demonstrated markedly superior predictive performance [area under the curve (AUC) = 0.940] compared with logistic regression (AUC = 0.791). These models offer clinicians a practical tool for early identification of high-risk patients, enabling timely, targeted interventions to mitigate infection-related complications and improve postoperative outcomes. |
| Publish Date |
2025-12-19 10:39 |
| Citation |
Wang YF, Han K, An N, Sun YN, Gao F, Sun Y, Zhang D, Zhao ZF, Guo Q, Gu JN, Yang Z. Risk prediction of biliary infection after endoscopic drainage for malignant perihilar biliary obstruction: A 10-year multicenter retrospective study. World J Gastroenterol 2025; 31(47): 113156 |
| URL |
https://www.wjgnet.com/1007-9327/full/v31/i47/113156.htm |
| DOI |
https://dx.doi.org/10.3748/wjg.v31.i47.113156 |
