Ignite Creation Date:
2025-12-25 @ 1:27 AM
Ignite Modification Date:
2025-12-27 @ 6:28 AM
Study NCT ID:
NCT06265493
Status:
COMPLETED
Last Update Posted:
2024-09-24
First Post:
2024-02-11
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Postoperative Infectious Complications Calculator for Elderly Patients
Sponsor:
Weidong Mi
Organization:
Study Overview
Official Title:
Postoperative Infectious Complications Calculator for Elderly Patients--A Derivation and External Validation of Prediction Models Based on Two Centers Large Sample
Status:
COMPLETED
Status Verified Date:
2024-09
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:
The investigators established a first-ever convenient scoring system for clinicians to assess the risk of Postoperative infectious complications (PICs) for elderly patients. Our scoring system can aid in the early detection of potential risks for postoperative infections. Higher-score patients were more likely to experience postoperative infections.
Detailed Description:
Background:
Postoperative infectious complications (PICs) are related to increased morbidity, mortality, and costs, especially in elderly patients. However, published prediction models of PICs are rarely based on elderly patients.
Objective:
The study wanted to identify practical and valuable variables that could be used to predict postoperative infections and establish a convenient scoring system for clinicians to assess the risk of such conditions in elderly patients.
Methods： Data from 2 population-based cohorts of elderly patients undergoing non-cardiac and non-neurology surgery were used to derive and validate multivariable logistic regression models. The risk prediction models were derived from 37230 patients hospitalized in the First Medical Center of the Chinese PLA General Hospital (January 2012 - August 2018). The risk prediction models were externally validated with data from a cohort of 10252 patients hospitalized in Henan Provincial People's Hospital (November 2014 to May 2022).
Postoperative infectious complications (PICs) are related to increased morbidity, mortality, and costs, especially in elderly patients. However, published prediction models of PICs are rarely based on elderly patients.
Objective:
The study wanted to identify practical and valuable variables that could be used to predict postoperative infections and establish a convenient scoring system for clinicians to assess the risk of such conditions in elderly patients.
Methods： Data from 2 population-based cohorts of elderly patients undergoing non-cardiac and non-neurology surgery were used to derive and validate multivariable logistic regression models. The risk prediction models were derived from 37230 patients hospitalized in the First Medical Center of the Chinese PLA General Hospital (January 2012 - August 2018). The risk prediction models were externally validated with data from a cohort of 10252 patients hospitalized in Henan Provincial People's Hospital (November 2014 to May 2022).
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?: