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

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.

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Key information

Conditions

Sepsis Infections Inflammation Pathologic Processes Pathological Conditions, Signs and Symptoms Postoperative Complications Systemic Inflammatory Response Syndrome

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

：

Patients undergoing major abdominal surgery.
The surgeon performing the operation has extensive experience in specialized surgeries such as upper gastrointestinal, hepatobiliary and pancreatic, colorectal, gynecological, and urological surgeries, having completed at least 50 corresponding specialized surgical cases.
The anesthesiologist performing the operation has more than 5 years of clinical experience.
All surgical patients receive general anesthesia.
Patients are aged ≥ 18 years. Exclusion Criteria：

Pregnancy-related surgeries (cesarean section, abortion surgery). 2. Patients with known preoperative infection or suspected infection. 3. Severely malnourished patients (BMI reference values are 17 kg/m² for patients < 70 years old and 17.8 kg/m² for patients > 70 years old).

Patients who have previously undergone abdominal surgery. 5. Patients without sufficient data, including demographic variables (such as age, gender), surgical details (surgery duration, surgical grade, anesthesia grade, anesthesia duration), and hospitalization details (such as ICU stay, in-hospital mortality).

Treatment and study plan

Exposure to major abdominal surgery

Procedure

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.

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.

Sponsors and collaborators

Lead sponsor

Xinhua Hospital, Shanghai Jiao Tong University School of Medicine

Other

Collaborators

Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine

Registry information

Official study title

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

Important dates

Study start: 2014
Primary completion: 2024
Study completion: 2024
First posted: Nov 12, 2024
Registry last updated: Nov 12, 2024

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Published trials that share one or more normalized conditions with this study.

Completed