Feeding Intolerance Risk Prediction Model in Patients With Enteral Nutrition Through Nasogastric Tube

Overview

To explore the risk factors of enteral feeding intolerance in critically ill patients, build a risk prediction model and verify it, in order to provide reference for early identification and screening of high-risk groups

Based on the previous literature study, the risk factors of enteral feeding intolerance in critically ill patients were obtained, and the general demographic, disease and treatment information of patients were collected. Four machine learning algorithms, namely traditional logistic regression, random forest, support vector machine and naive Bayes, were used to construct risk prediction models, and the optimal model was selected and verified by comparing the model performance

Conditions

Interventions

Eligibility

Outcomes