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Combining Biomarkers and Electronic Risk Scores to Predict AKI in Hospitalized Patients

NCT05988658 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 800

Last updated 2025-09-12

No results posted yet for this study

Summary

The study's objective is to evaluate the additive value of renal biomarkers (from blood and urine) for identifying individuals at high risk for severe acute kidney injury (AKI) above that of a novel natural language processing (NLP)-based AKI risk algorithm. The risk algorithm is based on electronic health records (EHR) data (labs, vitals, clinical notes, and test reports). Patients will enroll at the University of Chicago Medical Center and the University of Wisconsin Hospital, where the risk score will run in real time. The risk score will identify those patients with the highest risk for the future development of Stage 2 AKI and collect blood and urine for biomarker measurement over the subsequent 3 days.

Conditions

Interventions

DEVICE

ESTOP - AKI 2.0

Medical software as a Noninvasive medical device, which at the time of the project will not implement directly into subject/clinical care.

Sponsors & Collaborators

  • National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)

    collaborator NIH

  • University of Wisconsin, Madison

    collaborator OTHER

  • University of Chicago

    lead OTHER

Principal Investigators

  • Jay Koyner, MD · University of Chicago

  • Matthew Churpek, MD,MPH,PhD · University of Wisconsin, Madison

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2024-01-05
Primary Completion
2027-03-01
Completion
2028-03-01

Countries

  • United States

Study Locations

More Related Trials

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 NCT05988658 on ClinicalTrials.gov