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Pilot Study for Postoperative Machine Learning

NCT04877535 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 222

Last updated 2025-04-04

Study results available
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Summary

The objectives of the study are to determine the interpretability, workflow role, and effect on communications of showing report cards containing Machine Learning (ML)-based risk profiles based on pre- and intra-operative data to postoperative providers.

Conditions

  • Surgery--Complications

Interventions

DEVICE

ML-based report card

PACU and ward providers caring for participants will be notified by Anesthesia Control Tower clinicians before arrival if the patient's report card. The notification will contain a report card of the patient's forecast risk of major adverse events, explanatory machine-learning outputs, most influential pre- and intraoperative data, and predicted treatments.The ML risk profile generated for each patient will include risk of 30 day mortality, risk of respiratory failure, risk of acute kidney injury, and risk of postoperative delirium

Sponsors & Collaborators

  • National Center for Advancing Translational Sciences (NCATS)

    collaborator NIH

  • Washington University School of Medicine

    lead OTHER

Principal Investigators

  • Christopher R King, MD, PhD · Washington Univeristy School of Medicine

Study Design

Allocation
NON_RANDOMIZED
Purpose
OTHER
Masking
NONE
Model
PARALLEL

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2021-06-03
Primary Completion
2023-05-11
Completion
2023-05-11
FDA Device
Yes

Countries

  • United States

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 NCT04877535 on ClinicalTrials.gov