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Machine Learning Model to Predict Postoperative Respiratory Failure

NCT04527094 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 22250

Last updated 2022-09-01

No results posted yet for this study

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 intraoperative electronic health records, not administrative codes.

Conditions

  • Noncardiac Surgery

Interventions

DIAGNOSTIC_TEST

Prediction of postoperative respiratory failure using a machine learning

The performance of a machine learning model to predict postoperative respiratory failure after general anesthesia within postoperative day 7 was tested prospectively.

Sponsors & Collaborators

  • Seoul National University Hospital

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2021-05-26
Primary Completion
2022-05-25
Completion
2022-06-25

Countries

  • South Korea

Study Locations

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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 NCT04527094 on ClinicalTrials.gov