Risk prediction models for feeding intolerance in patients with enteral nutrition: a systematic review and meta-analysis

作者：Huijiao Chen, Jin H. Han, Jing Li, Jianhua Xiong, Dong Wang, Mingming Han, Yuehao Shen, Wenli Lu · 发表于：Frontiers in Nutrition · 年份：2025 · DOI：10.3389/fnut.2024.1522911 · 被引用次数：11 · 研究领域：Clinical Nutrition and Gastroenterology、Nutrition and Health in Aging、Child Nutrition and Water Access

Background: Although more risk prediction models are available for feeding intolerance in enteral-nourishment patients, it is still unclear how well these models will work in clinical settings. Future research faces challenges in validating model accuracy across populations, enhancing interpretability for clinical use, and overcoming dataset limitations. Objective: To thoroughly examine studies that have been published on feeding intolerance risk prediction models for enteral nutrition patients. Design: Conducted a systematic review and meta-analysis of observational studies. Methods: A comprehensive search of the literature was conducted using a range of databases, including China National Knowledge Infrastructure (CNKI), Wanfang Database, China Science and Technology Journal Database (VIP), SinoMed, PubMed, Web of Science, The Cochrane Library, Cumulative Index to Nursing and Allied Health Literature (CINAHL) and Embase. The search scope was confined to articles within the database from its inception until August 12th, 2024. The data from the selected studies should be extracted, including study design, subjects, duration of follow-up, data sources, outcome measures, sample size, handling of missing data, continuous variable handling methods, variable selection, final predictors, model development and performance, and form of model presentation. The applicability and bias risk were evaluated using the Prediction Model Risk of Bias Assessment Tool (PROBAST) checklist. Result...