Risk Factors Identification of Sepsis and Septic Shock After Major Abdominal Surgery Based on Artificial Intelligence
NCT ID: NCT06684340
Last Updated: 2024-11-12
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
22646 participants
OBSERVATIONAL
2014-01-01
2024-07-31
Brief Summary
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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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Detailed Description
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Conditions
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Study Design
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COHORT
RETROSPECTIVE
Interventions
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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.
Eligibility Criteria
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Inclusion Criteria
2. 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.
3. The anesthesiologist performing the operation has more than 5 years of clinical experience.
4. All surgical patients receive general anesthesia.
Exclusion Criteria
4\. 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).
18 Years
ALL
No
Sponsors
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Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine
OTHER
Xinhua Hospital, Shanghai Jiao Tong University School of Medicine
OTHER
Responsible Party
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Other Identifiers
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XH-24-009
Identifier Type: -
Identifier Source: org_study_id
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