Predicting Postoperative Pulmonary Infection in Elderly Patients Undergoing Major Surgery: a Study Based on Logistic Regression and Machine Learning Models

Completed

• Conditions: Postoperative Pulmonary Infection in Elderly Patients

• Registration Number: NCT06491459
• Lead Sponsor: Wuhan Union Hospital, China

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

Not available

Study Timeline

• Study Start: 2024-01-01
• Status Verified: 2024-06
• Primary Completion: 2024-06-01
• Study Completion: 2024-06-01
• Study First Submitted: 2024-06-27
• Study First Submitted QC: 2024-07-08
• Last Update Submitted: 2024-07-08
• Study First Posted: 2024-07-09
• Last Update Posted: 2024-07-09

Recruitment & Eligibility

• Status: COMPLETED
• Sex: All
• Target Recruitment: 9481

Inclusion Criteria

1. age ≥ 65 years
2. patients who were mechanically ventilated under major surgery

Exclusion Criteria

1. preoperative tracheal intubation
2. preoperative pneumonia
3. organ transplantation
4. missing data

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
the incidence of postoperative pulmonary infection during hospitalization	through study completion, an average of 30 days	the incidence of postoperative pulmonary infection during hospitalization

Trial Locations

Locations (1)

Union Hospital, Tongji Medical College, Huazhong University of Science and Technology; 🇨🇳 Wuhan, Hubei, China