Zhao JF, Jin GX, Wang Y, Huang XM. Intra-abdominal pressure and procalcitonin for prognosis in patients with severe acute pancreatitis: An etiology-based analysis. World J Gastrointest Surg 2025; 17(12): 111829 [DOI: 10.4240/wjgs.v17.i12.111829]
Corresponding Author of This Article
Guo-Xing Jin, Chief Physician, Department of General Surgery, Huzhou Wuxing District People's Hospital, Wuxing District Maternal and Child Health Hospital of Huzhou City, No. 1599 Dagang Road, Wuxing District, Huzhou 313000, Zhejiang Province, China. tony1128Lu@gmail.com
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
Retrospective Study
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/
Dec 27, 2025 (publication date) through Dec 25, 2025
Times Cited of This Article
Times Cited (0)
Journal Information of This Article
Publication Name
World Journal of Gastrointestinal Surgery
ISSN
1948-9366
Publisher of This Article
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
Share the Article
Zhao JF, Jin GX, Wang Y, Huang XM. Intra-abdominal pressure and procalcitonin for prognosis in patients with severe acute pancreatitis: An etiology-based analysis. World J Gastrointest Surg 2025; 17(12): 111829 [DOI: 10.4240/wjgs.v17.i12.111829]
World J Gastrointest Surg. Dec 27, 2025; 17(12): 111829 Published online Dec 27, 2025. doi: 10.4240/wjgs.v17.i12.111829
Intra-abdominal pressure and procalcitonin for prognosis in patients with severe acute pancreatitis: An etiology-based analysis
Jin-Feng Zhao, Guo-Xing Jin, Yao Wang, Xue-Ming Huang
Jin-Feng Zhao, Guo-Xing Jin, Xue-Ming Huang, Department of General Surgery, Huzhou Wuxing District People's Hospital, Wuxing District Maternal and Child Health Hospital of Huzhou City, Huzhou 313000, Zhejiang Province, China
Yao Wang, Department of General Surgery, Huzhou First People’s Hospital, Huzhou 313000, Zhejiang Province, China
Author contributions: Zhao JF performed the research, analyzed the data, and wrote the manuscript; Zhao JF and Jin GX designed the research study; Wang Y and Huang XM contributed to the data collection; All authors read and approved the final manuscript.
Supported by Huzhou Science and Technology Bureau Public Welfare Applied Research Project-General Medical and Health Program, No. 2021GY21.
Institutional review board statement: The Ethics Committee of Huzhou Wuxing District People’s Hospital determined that this retrospective study using deidentified data was exempt from full review per institutional guidelines for retrospective research using anonymized data.
Informed consent statement: The requirement for informed consent was waived by the Ethics Committee of Huzhou Wuxing District People’s Hospital because of the retrospective nature of this study and the use of anonymized data, in accordance with national regulations for retrospective research.
Conflict-of-interest statement: All authors report having no relevant conflicts of interest for this article.
Data sharing statement: The datasets generated and analyzed during the current study are available from the corresponding author at tony1128lu@gmail.com upon reasonable request. The data are anonymized, and the risk of identification is low. All data requests will be subject to institutional privacy review.
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: Guo-Xing Jin, Chief Physician, Department of General Surgery, Huzhou Wuxing District People's Hospital, Wuxing District Maternal and Child Health Hospital of Huzhou City, No. 1599 Dagang Road, Wuxing District, Huzhou 313000, Zhejiang Province, China. tony1128Lu@gmail.com
Received: July 10, 2025 Revised: September 17, 2025 Accepted: October 20, 2025 Published online: December 27, 2025 Processing time: 168 Days and 8.6 Hours
Abstract
BACKGROUND
Early risk stratification in severe acute pancreatitis (SAP) remains challenging with traditional scoring systems overlooking etiological heterogeneity, particularly in hypertriglyceridemic acute pancreatitis (HTG-AP).
AIM
To develop and evaluate a machine learning (ML) model combining intra-abdominal pressure (IAP) and procalcitonin (PCT) for SAP prognosis and evaluate its clinical impact across different etiologies.
METHODS
We retrospectively analyzed 245 patients with pancreatitis (98 patients with SAP). An ML model using 24-h peak IAP and PCT levels was used to predict 28-day mortality. Propensity score matching was used to compare IAP-PCT-guided management with conventional management.
RESULTS
The ML-IAP-PCT model outperformed the Acute Physiology and Chronic Health Evaluation II score (area under the curve: 0.853 vs 0.801, P = 0.044) and Bedside Index of Severity in Acute Pancreatitis score. IAP-PCT-guided management was associated with lower mortality (15.8% vs 25.0%, P = 0.043) and multiple organ dysfunction syndrome (48.7% vs 61.8%, P = 0.027) rates. Patients with HTG-AP showed the greatest benefit (multiple organ dysfunction syndrome: 39.3% vs 60.7%, P = 0.018).
CONCLUSION
ML-optimized IAP-PCT monitoring provides superior prognostic accuracy and guides management associated with improved outcomes, especially in patients with HTG-AP. Prospective validation is needed to establish causality for this etiology-stratified approach.
Core Tip: By integrating intra-abdominal pressure and procalcitonin using a machine learning algorithm, this study established a superior prognostic model for severe acute pancreatitis (AP). The core innovation, however, lies in revealing profound etiological heterogeneity. We demonstrated that the correlation between intra-abdominal pressure and procalcitonin and the benefits of guided management are most significant in patients with hypertriglyceridemic AP. These findings advocate for a shift from a uniform approach to an etiology-stratified precision medicine strategy, particularly for the high-risk hypertriglyceridemic AP subgroup.
