The prediction model for enteral feeding intolerance in intensive care unit patients:a scoping review
HUANG Long
LUO Chunfeng
ZHENG Wei
HUANG Ruijun
HE Ling
ZENG Fan
Abstract：Objective: To conduct a scope review of risk prediction models for enteral nutrition intolerance in critically ill patients, providing reference for clinical nursing practice and related research. Methods: Focused on risk prediction models for enteral nutrition intolerance in critically ill patients, systematically searched Chinese and English databases, with the search period from the establishment of the database to January 4, 2024. Two researchers independently screened the literature, extracted data, and evaluated the bias and applicability of the prediction models. Results: A total of 17 studies were included, involving 17 risk prediction models. The prevalence of enteral nutrition intolerance in critically ill patients ranged from 26.2% to 67.1%. The research design and construction methods of prediction models in this field are single, and the risk of bias is high. Most models were constructed using logistic regression analysis, with the area under the receiver operating characteristic curve (AUC) ranging from 0.700 to 0.906. Most prediction models lack external validation. Conclusion: Although the overall predictive performance of existing risk prediction models for enteral nutrition intolerance in critically ill patients is relatively good, they have a high risk of bias. Future research should explore the performance differences of prediction models constructed by different methods, reduce the risk of bias, and focus on external validation and clinical applicability.
Keywords：enteral nutritionprediction modelintensive care unitrisk assessmentscoping reviewnursing
Publication Date：2025-06-25
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：8( 2413-2420 )