Yang F, Windsor JA, Fu DL. Optimizing prediction models for pancreatic fistula after pancreatectomy: Current status and future perspectives. World J Gastroenterol 2024; 30(10): 1329-1345 [PMID: 38596504 DOI: 10.3748/wjg.v30.i10.1329]
Corresponding Author of This Article
Feng Yang, MD, PhD, Doctor, Surgeon, Department of Pancreatic Surgery, Huashan Hospital, Shanghai Medical College, Fudan University, No. 12 Central Urumqi Road, Shanghai 200040, China. yffudan98@126.com
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
Review
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (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: http://creativecommons.org/licenses/by-nc/4.0/
World J Gastroenterol. Mar 14, 2024; 30(10): 1329-1345 Published online Mar 14, 2024. doi: 10.3748/wjg.v30.i10.1329
Optimizing prediction models for pancreatic fistula after pancreatectomy: Current status and future perspectives
Feng Yang, John A Windsor, De-Liang Fu
Feng Yang, De-Liang Fu, Department of Pancreatic Surgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai 200040, China
John A Windsor, Surgical and Translational Research Centre, Faculty of Medical and Health Sciences, University of Auckland, Auckland 1142, New Zealand
Author contributions: Yang F collected the materials, discussed the topic, wrote the manuscript, and supervised this publication; Windsor JA and Fu DL discussed the topic and revised the manuscript.
Conflict-of-interest statement: We declare no conflicts of interest.
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/
Corresponding author: Feng Yang, MD, PhD, Doctor, Surgeon, Department of Pancreatic Surgery, Huashan Hospital, Shanghai Medical College, Fudan University, No. 12 Central Urumqi Road, Shanghai 200040, China. yffudan98@126.com
Received: December 5, 2023 Peer-review started: December 5, 2023 First decision: January 4, 2024 Revised: January 15, 2024 Accepted: February 25, 2024 Article in press: February 25, 2024 Published online: March 14, 2024
Core Tip
Core Tip: Postoperative pancreatic fistula (POPF) is a common complication following pancreatectomy, associated with increased morbidity and mortality. Optimizing prediction models for POPF is a critical focus in surgical research. Although over sixty models following pancreaticoduodenectomy have been documented, their predictive accuracy remains suboptimal across diverse populations. The validation of models after distal pancreatectomy is anticipated, while POPF prediction after central pancreatectomy requires further development and validation. Machine learning and big data analytics offer promising prospects for enhancing prediction model accuracy. Personalized prediction models and novel imaging technologies, such as AI-based radiomics, may further refine predictive models.
