Ignite Creation Date:
2024-05-06 @ 7:07 PM
Last Modification Date:
2024-10-26 @ 3:00 PM
Study NCT ID:
NCT05900167
Status:
NOT_YET_RECRUITING
Last Update Posted:
2023-06-12
First Post:
2023-06-02
Brief Title:
Feeding Intolerance Risk Prediction Model in Patients With Enteral Nutrition Through Nasogastric Tube
Sponsor:
Xiao Jie Chen
Organization:
RenJi Hospital
Study Overview
Official Title:
Feeding Intolerance Risk Prediction Model in Patients With Enteral Nutrition Through Nasogastric Tube
Status:
NOT_YET_RECRUITING
Status Verified Date:
2023-06
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
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
Detailed Description:
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
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None