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Cited by in CrossRef
For: Lu XM, Jia DS, Wang R, Yang Q, Jin SS, Chen L. Development of a prediction model for enteral feeding intolerance in intensive care unit patients: A prospective cohort study. World J Gastrointest Surg 2022; 14(12): 1363-1374 [PMID: 36632121 DOI: 10.4240/wjgs.v14.i12.1363]
URL: https://www.wjgnet.com/2150-5330/full/v14/i12/1363.htm
Number Citing Articles
1
Youquan Wang, Yanhua Li, Hongxiang Li, Nan Li, Xinyu Li, Dongfang Lv, Lingling Bao, Xuewen Feng, Lu Ke, Dong Zhang. External validation of the feeding intolerance prediction model (NOFI) in critically ill patients: A post hoc analysis of a large-scale randomized controlled trialJournal of Intensive Medicine 2026; 6(3): 239 doi: 10.1016/j.jointm.2025.12.004
2
Annette Bourgault, Ilana Logvinov, Chang Liu, Rui Xie, Jan Powers, Mary Lou Sole. Use of Machine Learning Models to Predict Microaspiration Measured by Tracheal Pepsin AAmerican Journal of Critical Care 2025; 34(1): 67 doi: 10.4037/ajcc2025349
3
Youquan Wang, Yanhua Li, Huimei Wang, Hongxiang Li, Yuting Li, Liying Zhang, Chaoyang Zhang, Meng Gao, Nan Zhang, Dong Zhang. Development and validation of a nomogram for predicting enteral feeding intolerance in critically ill patients (NOFI): Mixed retrospective and prospective cohort studyClinical Nutrition 2023; 42(12): 2293 doi: 10.1016/j.clnu.2023.10.003
4
Mingwei Zhong, Jianhuang Zheng, Ruwei Huang, Zhizhao Jiang, Yizhe Zhong. Exploring the incidence and influencing factors of acute gastrointestinal injury in ICU patients undergoing mechanical ventilation: a retrospective cohort studyBMC Research Notes 2026; 19(1) doi: 10.1186/s13104-026-07643-7
5
Hui Zhang, Yan Chen, Fan Li, Chaokai He, Xiaorong Li, Yu'e Wang, Junping Fan, Jinglan Wang, Ying Xia, Na Guo, Kunrong Yu. Efficacy and Tolerability of Non‐Routine Gastric Residual Volume Monitoring in Mechanically Ventilated Adults Receiving Early Enteral Nutrition: A Randomised Controlled Non‐Inferiority TrialNursing in Critical Care 2026; 31(3) doi: 10.1111/nicc.70486
6
Zhenfeng Zhou, Jicheng Zhang, Chunmei Fan, Zhengang Wei, Qi Wang, Congcong Liu. Risk prediction models for enteral nutrition feeding intolerance in critically ill patients: an overview of systematic reviewsFrontiers in Nutrition 2025; 12 doi: 10.3389/fnut.2025.1662409
7
Hui Yang, Jinmei Liu, Hongyan Sun. Risk prediction model for adult intolerance to enteral nutrition feeding – A literature reviewThe American Journal of the Medical Sciences 2025; 369(4): 427 doi: 10.1016/j.amjms.2024.11.012
8
Rong Yuan, Lei Liu, Jiao Mi, Xue Li, Fang Yang, Shifang Mao. Early prediction of enteral nutrition feeding intolerance risk in neurocritical patients and development of a simplified risk scoring tablesEuropean Journal of Clinical Nutrition 2026; 80(2): 159 doi: 10.1038/s41430-025-01683-1
9
Mette M. Berger, Annika Reintam Blaser, Orit Raphaeli, Pierre Singer. Early Feeding in Critical Care - Where Are We Now?Critical Care Clinics 2025; 41(2): 213 doi: 10.1016/j.ccc.2024.09.002
10
Huijiao Chen, Jin Han, Jing Li, Jianhua Xiong, Dong Wang, Mingming Han, Yuehao Shen, Wenli Lu. Risk prediction models for feeding intolerance in patients with enteral nutrition: a systematic review and meta-analysisFrontiers in Nutrition 2025; 11 doi: 10.3389/fnut.2024.1522911
11
Gülizar Demir Kıray, Gülten Karahan Okuroğlu. Enteral Feeding Intolerance Diagnostic Criteria And Current Approaches; Classic ReviewCURARE Journal of Nursing 2026; 0(10): 60 doi: 10.26650/CURARE.2026.1807990
12
Jing Xu, Wenyu Shi, Liying Xie, Jing Xu, Lanzheng Bian. Feeding Intolerance in Critically Ill Patients with Enteral Nutrition: A Meta-Analysis and Systematic ReviewThe Journal of Critical Care Medicine 2024; 10(1): 7 doi: 10.2478/jccm-2024-0007
13
Gaimei Wang, Cendi Lu, Owusu Mensah Solomon, Yujia Gu, Yijing Ling, Fanchi Xu, Yumin Tao, Yehong Wei. Construction and evaluation of a machine learning-based predictive model for enteral nutrition feeding intolerance risk in ICU patientsFrontiers in Nutrition 2025; 12 doi: 10.3389/fnut.2025.1600319
14
Weronika Walendziak, Karolina Domosud, Anna Malczyk, Damian Zienkiewicz, Gabriela Makulec, Kacper Ściebura, Magdalena Ostaszewska, Natalia Mordal, Wiktoria Wiśniewska, Milena Majchrzyk. Standardized, Individualized, or AI-Based Approach to Parenteral Nutrition in Neonatal Intensive Care Units: A Narrative ReviewCureus 2026;  doi: 10.7759/cureus.105328
15
Lijie Liu, Jin Li, Liting Hu, Xiaowei Cai, Xiaoyan Li, Yang Bai. Development and Validation of a Prediction Model for Enteral Feeding Intolerance in Critical Ill Patients: A Retrospective Cohort StudyJournal of Clinical Nursing 2025; 34(6): 2336 doi: 10.1111/jocn.17660
16
Pierre Singer, Eyal Robinson, Orit Raphaeli. Gastrointestinal failure, big data and intensive careCurrent Opinion in Clinical Nutrition & Metabolic Care 2023; 26(5): 476 doi: 10.1097/MCO.0000000000000961
17
Pierre Singer, Eyal Robinson, Orit Raphaeli. The future of artificial intelligence in clinical nutritionCurrent Opinion in Clinical Nutrition & Metabolic Care 2024; 27(2): 200 doi: 10.1097/MCO.0000000000000977
18
Miriam Theilla, Orit Raphaeli, Eyal Robinson, Pierre Singer. Nutrition, Metabolism and Kidney Support2024; : 149 doi: 10.1007/978-3-031-66541-7_14
19
Ying Lin, Xiaomin Wang, Lingyan Li, Yun Gou, Liping Zhang, Lijing Wang, Junhong Yang. Nomogram to predict feeding intolerance in critically ill childrenEuropean Journal of Pediatrics 2023; 182(12): 5293 doi: 10.1007/s00431-023-05205-8
20
Xiagang Luan, Yu Lin, Lingling Ke, Junhui Xu, Maomao Xi, Yong Xia, Deyun Wang. Individualized Implementation of Enteral Nutrition Adjusted by Laboratory Indicators and Clinical Parameter ScoringJournal of Burn Care & Research 2026; 47(2): 558 doi: 10.1093/jbcr/iraf194
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