Observational Study
Copyright ©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastrointest Surg. Dec 27, 2022; 14(12): 1363-1374
Published online Dec 27, 2022. doi: 10.4240/wjgs.v14.i12.1363
Development of a prediction model for enteral feeding intolerance in intensive care unit patients: A prospective cohort study
Xue-Mei Lu, Deng-Shuai Jia, Rui Wang, Qing Yang, Shan-Shan Jin, Lan Chen
Xue-Mei Lu, Deng-Shuai Jia, School of Nursing, Shanghai Jiao Tong University, Shanghai 200025, China
Xue-Mei Lu, Lan Chen, Department of Nursing, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai 200080, China
Rui Wang, Qing Yang, Shan-Shan Jin, Department of Critical Care Medicine, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai 200080, China
Author contributions: Lu XM contributed to conceptualization, methodology, formal analysis, investigation, data curation, writing the original draft, and project administration; Jia DS contributed to conceptualization, methodology, investigation, and writing the original draft; Wang R and Yang Q contributed to methodology, investigation, and resources; Jin SS contributed to investigation and resources; Chen L contributed to conceptualization, methodology, resources, review and editing of the manuscript, supervision, and project administration; All authors read and approved the final manuscript.
Institutional review board statement: The study protocol was approved (numbered 2020KY230) by the appropriate ethics committee (Medical Ethics Committee of Shanghai General Hospital) on December 23, 2020.
Informed consent statement: Before we enrolled patients, informed consent was obtained from the patient or next of kin. Since we needed to complete daily ultrasonography of patients, we needed to obtain their informed consent.
Conflict-of-interest statement: The authors declare having no conflicts of interest.
Data sharing statement: If there is a need to get the dataset, please contact Xue-Mei Lu (lu_xm1118@163.com). The information of the patients in the dataset is anonymized.
STROBE statement: The authors have read the STROBE Statement–checklist of items, and the manuscript was prepared and revised according to the STROBE Statement–checklist of items.
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: Lan Chen, PhD, Chief Nurse, Department of Nursing, Shanghai General Hospital, Shanghai Jiao Tong University, No. 86 Wu Jin Road, Shanghai 200080, China. 13636317690@126.com
Received: August 27, 2022
Peer-review started: August 27, 2022
First decision: September 25, 2022
Revised: October 15, 2022
Accepted: November 16, 2022
Article in press: November 16, 2022
Published online: December 27, 2022
Processing time: 122 Days and 2.6 Hours
Core Tip

Core Tip: Enteral nutrition (EN) is an essential piece of providing care to critically ill patients. However, some patients will experience complications related to EN and become intolerant to this nutritional support. In this study, we developed a model to predict patients who are at high risk of enteral feeding intolerance. In the future when an intensive care unit patient requires EN, nurses can distinguish whether the patient is a high-risk patient. Then, they can allocate their time to more observation of the high-risk patient to discover the patient’s complications and administer effective measures in advance. In the long-term, this strategy will reduce the workload of the nursing staff and will achieve more accurate care.