ReviewFrontiers in nutrition2025
Risk prediction models for enteral nutrition feeding intolerance in critically ill patients: an overview of systematic reviews.
Review in Frontiers in nutrition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed.
- Observational
- Risk stratification of postoperative enteral feeding intolerance using explainable machine learning in oral cancer free flap reconstruction.Frontiers in nutrition · 2026Article
- Precision nutrition in critical illness: a phase-specific framework from acute feeding to post-ICU recovery.Frontiers in nutrition · 2026Review
- Advancements in research on feeding intolerance to enteral nutrition in neurocritical patients undergoing sedation and analgesia.Frontiers in nutrition · 2026Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.