Retrospective Study
Copyright ©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Apr 21, 2022; 28(15): 1588-1600
Published online Apr 21, 2022. doi: 10.3748/wjg.v28.i15.1588
Development and validation of a prediction model for moderately severe and severe acute pancreatitis in pregnancy
Du-Jiang Yang, Hui-Min Lu, Yong Liu, Mao Li, Wei-Ming Hu, Zong-Guang Zhou
Du-Jiang Yang, Yong Liu, Zong-Guang Zhou, Department of Gastroenterological Surgery, West China Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China
Hui-Min Lu, Mao Li, Wei-Ming Hu, Department of Pancreatic Surgery, West China Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China
Author contributions: Yang DJ and Zhou ZG conception and design; Lu HM, Liu Y, Li M, and WH collection data; Yang DJ, Lu HM, and Zhou ZG analysis data; Yang DJ write the manuscript; Hu WM and Zhou ZG revised the manuscript.
Supported by the 1.3.5 Project for Disciplines of Excellence, West China Hospital, Sichuan University No. ZYGD20006 and ZYJC18027.
Institutional review board statement: This study was reviewed and approved by the Institutional Ethics Committee of the West China Hospital.
Informed consent statement: Patients were not required to give informed consent to the study because the analysis used anonymous clinical data that were obtained after each patient agreed to treatment by written consent.
Conflict-of-interest statement: There are no conflicts of interest to report.
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: Zong-Guang Zhou, FACS, PhD, Chief Doctor, Department of Gastroenterological Surgery, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu 610041, Sichuan Province, China. zhou767@163.com
Received: November 20, 2021
Peer-review started: November 20, 2021
First decision: January 11, 2022
Revised: February 2, 2022
Accepted: March 6, 2022
Article in press: March 6, 2022
Published online: April 21, 2022
Abstract
BACKGROUND

The severity of acute pancreatitis in pregnancy (APIP) is correlated with higher risks of maternal and fetal death.

AIM

To develop a nomogram that could predict moderately severe and severe acute pancreatitis in pregnancy (MSIP).

METHODS

Patients with APIP admitted to West China Hospital between January 2012 and December 2018 were included in this study. They were divided into mild acute pancreatitis in pregnancy (MAIP) and MSIP. Characteristic parameters and laboratory results were collected. The training set and test set were randomly divided at a ratio of 7:3. Least absolute shrinkage and selection operator regression was used to select potential prognostic factors. A nomogram was developed by logistic regression. A random forest model was used to validate the stability of the prediction factors. Receiver operating characteristic curves and calibration curves were used to evaluate the model’s predictive performance.

RESULTS

A total of 190 patients were included in this study. A total of 134 patients (70.5%) and 56 patients (29.5%) were classified as having MAIP and MSIP, respectively. Four independent predictors (lactate dehydrogenase, triglyceride, cholesterol, and albumin levels) were identified for MSIP. A nomogram prediction model based on these factors was established. The model had areas under the curve of 0.865 and 0.853 in the training and validation sets, respectively. The calibration curves showed that the nomogram has a good consistency.

CONCLUSION

A nomogram including lactate dehydrogenase, triglyceride, cholesterol, and albumin levels as independent predictors was built with good performance for MSIP prediction.

Keywords: Acute pancreatitis, Prediction model, Pregnancy, Severity, Nomogram, Random forest

Core Tip: The severity of acute pancreatitis in pregnancy (APIP) is correlated with higher risks of maternal and fetal death. Few studies have focused on APIP severity prediction. We identified four predictors developed and established a prediction nomogram model for pregnant patients with moderate and severe acute pancreatitis. This model achieved good concordance indexes and may help guide doctors in the managementof APIP.