Status:
COMPLETED
Machine Learning Model to Predict Postoperative Respiratory Failure
Lead Sponsor:
Seoul National University Hospital
Conditions:
Noncardiac Surgery
Eligibility:
All Genders
18+ years
Brief Summary
The main objective of this study is to develop a machine learning model that predicts postoperative respiratory failure within 7 postoperative day using a real-world, local preoperative and intraopera...
Detailed Description
Postoperative pulmonary complications are known to increase the length of hospital stay and healthcare cost. One of the most serious form of these complications is postoperative respiratory failure, w...
Eligibility Criteria
Inclusion
- Adults patients undergoing general anesthesia for noncardiac surgery
Exclusion
- Age under 18 years
- Surgery duration \< 1 hr
- Cardiac surgery
- Surgery performed only regional or local anesthesia, peripheral nerve block, or monitored anesthesia care
- Organ transplantation
- Patient with preoperative tracheal intubation
- Patients who had tracheostoma prior to surgery
- Patients scheduled for tracheostomy
- Surgery performed outside the operating room
- Length of hospital stay \< 24 h
- If the patients had multiple surgeries during the same hospital stays, we included the first surgical cases in the dataset.
Key Trial Info
Start Date :
May 26 2021
Trial Type :
OBSERVATIONAL
Allocation :
ACTUAL
End Date :
June 25 2022
Estimated Enrollment :
22250 Patients enrolled
Trial Details
Trial ID
NCT04527094
Start Date
May 26 2021
End Date
June 25 2022
Last Update
September 1 2022
Active Locations (1)
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1
Hyun-Kyu Yoon
Seoul, South Korea