NCT06684340

Risk Factors Identification of Sepsis and Septic Shock After Major Abdominal Surgery Based on Artificial Intelligence

Construction of AI-enabled Models for Predicting the Risk of Sepsis After Major Abdominal Surgery: a Retrospective Multicenter Clinical Study

• Status: Completed
• Phase: —
• Study type: Observational
• Enrollment: 22,646 (actual)
• Sponsor: Xinhua Hospital, Shanghai Jiao Tong University School of Medicine · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Not accepted

Summary

The goal of this observational study is to identify the risk factors and build the early warning system of sepsis and septic shock after major abdominal surgery based on artificial intelligence. The main questions it aims to answer are: What are the high risk factors of postoperative sepsis? Which factors can accelerate the progression of sepsis? Researchers will collect perioperative characteristics to construct predictive models of postoperative sepsis in a retrospective abdominal surgical population based on artificial intelligence, and the accuracy of the models were tested in an external dataset.

Conditions

• Sepsis
• Postoperative Complications

Interventions

Type	Name	Description
PROCEDURE	Exposure to major abdominal surgery	This study is a retrospective cohort study. The 'exposure' situation is based on historical records and observation, and no active intervention has been conducted on the study subjects to change their exposure status.

Timeline

• Start date: 2014-01-01
• Primary completion: 2024-06-30
• Completion: 2024-07-31
• First posted: 2024-11-12
• Last updated: 2024-11-12