Ignite Creation Date:
2025-12-24 @ 2:45 PM
Ignite Modification Date:
2026-01-12 @ 6:54 AM
Study NCT ID:
NCT06491459
Status:
COMPLETED
Last Update Posted:
2024-07-09
First Post:
2024-06-27
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Predicting Postoperative Pulmonary Infection in Elderly Patients Undergoing Major Surgery: a Study Based on Logistic Regression and Machine Learning Models
Sponsor:
Union Hospital, Tongji Medical College, Huazhong University of Science and Technology
Organization:
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:
False
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?: