Acute Kidney Injury Clinical Trial
— ORACLEOfficial title:
Perioperative Outcome Risk Assessment With Computer Learning Enhancement
Verified date | November 2022 |
Source | Washington University School of Medicine |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Interventional |
This study will test whether anesthesiology clinicians working in a telemedicine setting can predict patient risk for postoperative complications (death and acute kidney injury) more accurately with access to a machine learning display than without it.
Status | Completed |
Enrollment | 5114 |
Est. completion date | November 1, 2022 |
Est. primary completion date | November 1, 2022 |
Accepts healthy volunteers | No |
Gender | All |
Age group | 18 Years and older |
Eligibility | Inclusion Criteria: - Surgery in the main operating suite at Barnes-Jewish Hospital - Surgery during hours of ACT operation (weekdays 7:00am-4:00pm) - Enrolled in the TECTONICS randomized clinical trial (NCT03923699) Exclusion Criteria: - None |
Country | Name | City | State |
---|---|---|---|
United States | Washington University School of Medicine | Saint Louis | Missouri |
Lead Sponsor | Collaborator |
---|---|
Washington University School of Medicine | Foundation for Anesthesia Education and Research |
United States,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Area under receiver-operating characteristic curve of clinician prediction for postoperative death | Clinicians will predict the likelihood of postoperative death for each case using a categorical scale. A logistic regression will be constructed using the clinician predictions as inputs, and the area under the receiver-operating characteristic curve will be determined. | 30 days | |
Primary | Area under receiver-operating characteristic curve of clinician prediction for postoperative acute kidney injury | Clinicians will predict the likelihood of postoperative acute kidney injury for each case using a categorical scale. A logistic regression will be constructed using the clinician predictions as inputs, and the area under the receiver-operating characteristic curve will be determined. | 7 days |
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