Retrospective Study
Copyright ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Cases. Aug 26, 2024; 12(24): 5502-5512
Published online Aug 26, 2024. doi: 10.12998/wjcc.v12.i24.5502
Assessment of early factors for identification or prediction severe acute pancreatitis in pregnancy
Li-Fen Mei, Quan Gan, Jing Hu, Yun-Xiang Li, Rui Tian, Cheng-Jian Shi
Li-Fen Mei, Quan Gan, Jing Hu, Yun-Xiang Li, Department of Critical Care Medicine, Maternal and Child Health Hospital of Hubei Province, Wuhan 430000, Hubei Province, China
Rui Tian, Cheng-Jian Shi, Department of Biliary-Pancreatic Surgery, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei Province, China
Co-corresponding authors: Rui Tian and Cheng-Jian Shi.
Author contributions: Tian R and Shi CJ conceptualized and designed the research; Mei LF, Gan Q, Hu J, and Li YX screened patients and acquired clinical data; Mei LF, Tian R, and Shi CJ performed the data analysis; Mei LF, Tian R, and Shi CJ wrote the paper; All authors read and approved the final manuscript. Mei LF acquired clinical data, performed data analysis, and prepared the first draft of the manuscript. She has made crucial and indispensable contributions towards the completion of the project and thus qualified as one of the first authors of the paper. Both Tian R and Shi CJ have played important and indispensable roles in the research design, data interpretation, and manuscript preparation as the co-corresponding authors. Shi CJ conceptualized, designed, and supervised the whole process of the project. He searched the literature and revised and submitted the early version of the manuscript. Tian R was instrumental and responsible for data re-analysis and re-interpretation, figure plotting, the comprehensive literature search, and preparation and submission of the current version of the manuscript. This collaboration between Tian R and Shi CJ was crucial for the publication of this manuscript.
Institutional review board statement: The study was reviewed and approved by the Ethics Committee of Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology and the Ethics Committee of Maternal and Child Health Hospital of Hubei Province (Approval No.: TJ-IRB202404002 and 2023IEC097).
Informed consent statement: Technical records and data did not include potential patient identifying information and therefore did not require informed consent.
Conflict-of-interest statement: All authors have no conflicts of interest to declare.
Data sharing statement: No additional data are available.
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: Cheng-Jian Shi, PhD, Affiliate Associate Professor, Surgeon, Department of Biliary-Pancreatic Surgery, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, No. 1095 Jiefang Avenue, Wuhan 430030, Hubei Province, China. chengj1010@sina.com
Received: April 28, 2024
Revised: May 25, 2024
Accepted: June 20, 2024
Published online: August 26, 2024
Processing time: 73 Days and 20.4 Hours
Abstract
BACKGROUND

Acute pancreatitis in pregnancy (APIP) is a rare and serious condition, and severe APIP (SAPIP) can lead to pancreatic necrosis, abscess, multiple organ dysfunction, and other adverse maternal and infant outcomes. Therefore, early identification or prediction of SAPIP is important.

AIM

To assess factors for early identification or prediction of SAPIP.

METHODS

The clinical data of patients with APIP were retrospectively analyzed. Patients were classified with mild acute pancreatitis or severe acute pancreatitis, and the clinical characteristics and laboratory biochemical indexes were compared between the two groups. Logical regression and receiver operating characteristic curve analyses were performed to assess the efficacy of the factors for identification or prediction of SAPIP.

RESULTS

A total of 45 APIP patients were enrolled. Compared with the mild acute pancreatitis group, the severe acute pancreatitis group had significantly increased (P < 0.01) heart rate (HR), hemoglobin, neutrophil ratio (NEUT%), and neutrophil–lymphocyte ratio (NLR), while lymphocytes were significantly decreased (P < 0.01). Logical regression analysis showed that HR, NEUT%, NLR, and lymphocyte count differed significantly (P < 0.01) between the groups. These may be factors for early identification or prediction of SAPIP. The area under the curve of HR, NEUT%, NLR, and lymphocyte count in the receiver operating characteristic curve analysis was 0.748, 0.732, 0.821, and 0.774, respectively. The combined analysis showed that the area under the curve, sensitivity, and specificity were 0.869, 90.5%, and 70.8%, respectively.

CONCLUSION

HR, NEUT%, NLR, and lymphocyte count can be used for early identification or prediction of SAPIP, and the combination of the four factors is expected to improve identification or prediction of SAPIP.

Keywords: Severe acute pancreatitis in pregnancy; Early identification factors; Early predictive factors; Clinical features; Laboratory biochemical index

Core Tip: This retrospective study explored factors for early identification or prediction of severe acute pancreatitis in pregnancy (SAPIP). A total of 45 APIP patients were enrolled. Logistic regression analysis showed that heart rate, neutrophil ratio, neutrophil–lymphocyte ratio, and lymphocyte count were significantly correlated with SAPIP. These four indexes showed valuable area under the curve, sensitivity, and specificity through receiver operating characteristic curve analysis. These results suggested that heart rate, neutrophil ratio, neutrophil-lymphocyte ratio, and lymphocyte count can be used for early identification or prediction of SAPIP.