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

NCT06684340 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 22646

Last updated 2024-11-12

No results posted yet for this study

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

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.

Sponsors & Collaborators

  • Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine

    collaborator OTHER

  • Xinhua Hospital, Shanghai Jiao Tong University School of Medicine

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2014-01-01
Primary Completion
2024-06-30
Completion
2024-07-31

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06684340 on ClinicalTrials.gov