Using Machine-Learning to Assess the Prognostic Value of Early Enteral Feeding Intolerance in Critically Ill Patients: A Retrospective Study

Using Machine-Learning to Assess the Prognostic Value of Early Enteral Feeding Intolerance in Critically Ill Patients: A Retrospective Study

Background: The association between gastrointestinal intolerance during early enteral nutrition (EN) and adverse clinical outcomes in critically ill patients is controversial. We aimed to assess the prognostic value of enteral feeding intolerance (EFI) markers during early ICU stays and to predict e...

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Bibliographic Details
Main Authors: Orit Raphaeli, Liran Statlender, Chen Hajaj, Itai Bendavid, Anat Goldstein, Eyal Robinson, Pierre Singer
Format: Article
Language:English
Published: MDPI AG 2023-06-01
Series:Nutrients
Subjects:
enteral nutrition
gastrointestinal intolerance
enteral feeding intolerance
machine learning
prediction models
Online Access:https://www.mdpi.com/2072-6643/15/12/2705

Internet

https://www.mdpi.com/2072-6643/15/12/2705

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