NCT06415630

Prediction Models for Postoperative Reintubation in Patients With Acute Aortic Dissection

Multiple Automated Machine-learning Prediction Models for Postoperative Reintubation in Patients With Acute Aortic Dissection

• Status: Completed
• Phase: —
• Study type: Observational
• Enrollment: 861 (actual)
• Sponsor: Union Hospital, Tongji Medical College, Huazhong University of Science and Technology · Academic / Other
• Sex: All
• Age: 19 Years – 90 Years
• Healthy volunteers: —

Summary

Reintubation is an adverse postoperative complication in patients with Type A aortic dissection (AAD) that correlates to poor outcomes. This study aims to analyze the risk factors associated with reintubation and to create a fully automated score model to predict the incidence of reintubation. A total of 861 patients diagnosed with AAD and undergoing surgical procedures in a single institution between January 2018 and October 2023 were selected in wuhan Union Hospital. Preoperative and postoperative informmation was used for seeking risk factors and build prediction model for postoperative reintubation. Finally, 5 risk factors wasidentified and a nomogram was established for predicting postoperative reintubation in patients with AAD.

Conditions

• Nomogram
• Prediction Model
• Type A Aortic Dissection
• Postoperative Reintubation

Interventions

Type	Name	Description
PROCEDURE	Type A aortic dissection surgery	Patients with type A aortic dissection undergone surgery.

Timeline

• Start date: 2018-01-01
• Primary completion: 2023-10-31
• Completion: 2023-12-31
• First posted: 2024-05-16
• Last updated: 2024-05-16

Locations

1 site across 1 country: China