NCT05671926

Different Algorithm Models to Predict Postoperative Pneumonia in Elderly Patients

• Status: Unknown
• Phase: —
• Study type: Observational
• Enrollment: 10,000 (estimated)
• Sponsor: Union Hospital, Tongji Medical College, Huazhong University of Science and Technology · Academic / Other
• Sex: All
• Age: 65 Years
• Healthy volunteers: —

Summary

The researchers aim to compare different algorithms to predict postoperative pneumonia in elderly patients and to assess the risk of pneumonia in elderly patients.

Detailed description

Postoperative pneumonia is a common complication that increases the mortality and length of older patients. In order to better assess the risk of postoperative pneumonia in elderly patients, we plan to use database information and different algorithms, such as logistic regression, random forest, and other algorithms respectively to build models and evaluate the effects of the models.

Conditions

• Postoperative Pulmonary Complications

Timeline

• Start date: 2023-01-01
• Primary completion: 2023-02-01
• Completion: 2023-02-01
• First posted: 2023-01-05
• Last updated: 2023-01-05