Risk prediction models for enteral nutrition feeding intolerance in critically ill patients: an overview of systematic reviews
Year: 2025
Type: review
Study design: Systematic Review
Abstract: Objective: To evaluate the systematic reviews of a risk prediction model for enteral nutrition feeding intolerance in critically ill patients. Methods: We registered the protocol for this overview in PROSPERO. Computer searches were conducted on the PubMed, Embase, Web of Science, Cochrane Library, CINAHL, Embase databases China National Knowledge Infrastructure (CNKI), Wanfang Database and SinoMed to search for systematic reviews related to the study. Two investigators independently screened the literature, extracted information, and used the Risk of Bias in Systematic Reviews (ROBIS) tool to assess the risk of bias of the retrieved systematic reviews. Results: Eight systematic reviews were included, total of 115 prediction models, with more than half of the predictive models (71/115 = 61.7%) having undergone internal validation and a small number (36/115 = 31.3%) having undergone external validation. Of the quality evaluations, two were at low risk of bias, six were at high risk, and the overall risk of bias was high. Discussion: The completeness of reporting and methodological quality of systematic reviews of prediction models for enteral nutrition feeding intolerance in critically ill patients were inconsistent and lacked specific quality standards. There is an urgent need for standardized reporting and quality criteria to improve the quality of prediction models for enteral nutrition feeding intolerance in ICU patients.
Source: Frontiers in Nutrition
Authors: Zhenfeng Zhou, Jicheng Zhang, Chunmei Fan, Zhengang Wei, Qi Wang, Congcong Liu
Language: English
Subfield: Nutrition and Dietetics
Field: Nursing
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W4414716969