Copyright ©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Nov 28, 2022; 28(44): 6206-6212
Published online Nov 28, 2022. doi: 10.3748/wjg.v28.i44.6206
Medical imaging for pancreatic diseases: Prediction of severe acute pancreatitis complicated with acute respiratory distress syndrome
Ling-Ji Song, Bo Xiao
Ling-Ji Song, Bo Xiao, Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, Sichuan Province, China
Author contributions: Xiao B designed the research study; Song LJ and Xiao B performed the research, analyzed the data, and wrote the manuscript; and all authors have read and approved the final manuscript.
Supported by the Nanchong City College Cooperative Research Project, No. 19SXHZ0282; and Medical Imaging Key Laboratory of Sichuan Province, No MIKLSP202008.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
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: Bo Xiao, MD, PhD, Associate Professor, Doctor, Teacher, Department of Radiology, Affiliated Hospital of North Sichuan Medical College, No. 1 Maoyuan South Street, Nanchong 637000, Sichuan Province, China. xiaoboimaging@163.com
Received: September 12, 2022
Peer-review started: September 12, 2022
First decision: October 4, 2022
Revised: October 15, 2022
Accepted: November 17, 2022
Article in press: November 17, 2022
Published online: November 28, 2022

In this editorial we comment on the article published in the recent issue of the World Journal of Gastroenterology [2022; 28 (19): 2123-2136]. We pay attention to how to construct a simpler and more reliable new clinical predictive model to early identify patients at high risk of acute respiratory distress syndrome (ARDS) associated with severe acute pancreatitis (SAP), and to early predict the severity of organ failure from chest computed tomography (CT) findings in SAP patients. As we all know, SAP has a sudden onset, is a rapidly changing condition, and can be complicated with ARDS and even multiple organ dysfunction syndrome, and its mortality rate has remained high. At present, there are many clinical scoring systems for AP, including the bedside index for severity in AP, acute physiology and chronic health evaluation II, systemic inflammatory response syndrome, Japanese severe score, quick sepsis-related organ failure assessment, etc. However, some of these scoring systems are complex and require multiple and difficult clinical parameters for risk stratification. Although the aforementioned biomarkers are readily available, their ability to predict ARDS varies. Accor-dingly, it is extremely necessary to establish a simple and valuable novel model to predict the development of ARDS in AP. In addition, the extra-pancreatic manifestations of AP patients often involve the chest, among which pleural effusion and pulmonary consolidation are the more common complications. Therefore, by measuring the semi-quantitative indexes of chest CT in AP patients, such as the amount of pleural effusion and the number of lobes involved as pulmonary consolidation, it has important reference value for the early diagnosis of SAP complicated with ARDS and is expected to provide a basis for the early treatment of ARDS.

Keywords: Severe acute pancreatitis, Acute respiratory distress syndrome, Clinical scoring system, Prediction model, Semi-quantitative

Core Tip: Respiratory failure has been confirmed to be the most common type of organ failure in acute pancreatitis (AP) and is closely related to high mortality. Acute respiratory distress syndrome (ARDS) is one of the most common patterns of respiratory failure in AP and is still a little-known disease. Although some studies have shown that it is promising to predict the results of AP-related ARDS, the preventive strategies for ARDS development are still in their infancy. For this reason, we need to establish a simple and valuable new prediction model, combined with chest computed tomography findings, to early identify high-risk patients with severe AP and ARDS and help clinicians take timely intervention measures to prevent disease progression.