Viewing Study NCT06491459



Ignite Creation Date: 2024-07-17 @ 11:14 AM
Last Modification Date: 2024-10-26 @ 3:34 PM
Study NCT ID: NCT06491459
Status: COMPLETED
Last Update Posted: 2024-07-09
First Post: 2024-06-27

Brief Title: Predicting Postoperative Pulmonary Infection in Elderly Patients Undergoing Major Surgery a Study Based on Logistic Regression and Machine Learning Models
Sponsor: Wuhan Union Hospital China
Organization: Wuhan Union Hospital China

Study Overview

Official Title: Predicting Postoperative Pulmonary Infection in Elderly Patients Undergoing Major Surgery a Study Based on Logistic Regression and Machine Learning Models
Status: COMPLETED
Status Verified Date: 2024-06
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: Although a number of clinical predictive models were developed to predict postoperative pulmonary infection few predictive models have been used in elderly patients In this study the researchers aim to compare different algorithms to predict postoperative pulmonary infection in elderly patients and to assess the risk of postoperative pulmonary infection in elderly patients
Detailed Description: None

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