Construction of AI-enabled Models for Predicting the Risk of Sepsis After Major Abdominal Surgery: a Retrospective Multicenter Clinical Study
Overview
- Phase
- N/A
- Intervention
- Not specified
- Conditions
- Sepsis
- Sponsor
- Xinhua Hospital, Shanghai Jiao Tong University School of Medicine
- Enrollment
- 22646
- Primary Endpoint
- Sepsis within 28 days after surgery.
- Status
- Completed
- Last Updated
- last year
Overview
Brief 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.
Investigators
Eligibility Criteria
Inclusion Criteria
- Not provided
Exclusion Criteria
- Not provided
Outcomes
Primary Outcomes
Sepsis within 28 days after surgery.
Time Frame: In the 28-day period following surgery
For patients within 28 days after surgery, if there is a recorded or suspected infection and the Sequential Organ Failure Assessment (SOFA) score is ≥ 2 points, sepsis can be diagnosed. For sepsis patients, if they still have persistent hypotension after adequate volume resuscitation and require vasopressor drugs to maintain a Mean Atrial Pressure (MAP) ≥ 65 mmHg and a serum lactate level \> 2 mmol/L, it is considered that the sepsis patient has progressed to septic shock.