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

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.

Study Overview

• Status: Recruiting
• Conditions: Biomarkers; Acute Kidney Injury
• Intervention / Treatment: Device: ESTOP - AKI 2.0

Detailed Description

The investigators hypothesize that combining the biomarkers with electronic health risk score will impact improvement in AKI risk stratification. Using a real time, externally validated electronic health record based AKI risk score, the investigators will enroll patients who are at high risk for the impending development of KDIGO Stage 2 AKI (top 10% of risk). Once identified and enrolled, patients will have blood and urine samples collected over the next 3 days. The investigators will recruit two cohorts of 400 patients across the two institutions. In the development cohort, the investigators will see if adding urinary or blood biomarkers of AKI can improve the ability of EHR-risk score to predict the development of Stage 2 AKI and other outcomes. The investigators will compare the area under the receiver operator characteristic curve (AUC) for the risk score alone versus the risk score plus biomarkers. The investigators will then seek to validate our findings in a separate cohort of 400 patients.

• Study Type: Observational
• Enrollment (Estimated): 800

Contacts and Locations

• Study Contact: Name: Jay Koyner, MD; Phone Number: 773-702-4842; Email: jkoyner@uchicago.edu

Study Locations

• United States
  • Illinois
    • Chicago, Illinois, United States, 60637
      • Recruiting
      • University of Chicago Medical Center
      • Contact: Aiman Fatima, MBBS; Phone Number: 773-702-6201; Email: aimanfatima@uchicagomedicine.org
      • Contact: Ola Anjorin, MBBS,DA,MPH; Phone Number: 773-704-3168; Email: oanjorin@bsd.uchicago.edu
      • Principal Investigator: Jay Koyner, MD
  • Wisconsin
    • Madison, Wisconsin, United States, 53792
      • Recruiting
      • University Of Wisconsin Hospital
      • Contact: Madeline Ogus, MS; Phone Number: 608-265-2878; Email: mkoguss@medicine.wisc.edu
      • Contact: Michael Weber; Phone Number: 608-263-3369; Email: mjweber@medicine.wisc.edu
      • Principal Investigator: Matthew Churpek, MD,MPH,PhD

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Probability Sample

Study Population

Adult patients admitted in inpatient ward, intermediate or ICU care at UCMC or UWHealth with E-STOP AKI 2.0 score in the top 10% of risk (historically from all hospitalized patients) within the last 12 hours. (First time across this 10% risk threshold during this hospital stay)

Description

Inclusion Criteria:

1. Age ≥ 18 years
2. E-STOP AKI 2.0 score in the top 10% of risk (historically from all hospitalized patients) within the last 12 hours. (First time across this 10% risk threshold during this hospital stay).
3. Admitted to an inpatient ward, intermediate, or ICU care at the University of Chicago Medical Center (UCMC) or University of Wisconsin Health (UWHealth). (No Emergency Department patients)
4. Patient or their legally authorized representative must be able to read, speak, and understand English, for the purposes of consenting. Otherwise, inclusion in this protocol will be done without regard to race, ethnic origin or gender

Exclusion Criteria:

1. Voluntary refusal or missing written consent of the patient / legal representative.
2. Patients with a known history of end-stage renal disease on dialysis (including renal transplantation).
3. Patients without a measured serum creatinine value during their inpatient stay.
4. Patients with a creatinine >4.0 mg/dl at the time of admission or available in the EHR from the last 6 months
5. Patients with prior episode of KDIGO defined AKI during this same hospitalization- regardless of E-STOP AKI 2.0 score
6. Patients with prior renal consultation during their admission.
7. Patient with an E-STOP AKI 2.0 above the top 10% risk threshold more than 12 hours ago during this same hospital stay.
8. Incarcerated patients
9. Pregnant patients

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
Study cohort; Patients will be identified as high risk based on their AKI risk score (ESTOP- AKI 2.0) being in the top 10% of all hospitalized patients	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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Developing KDIGO stage 2 AKI	Number of patients developing KDIGO Stage 2 AKI. KDIGO Stage 2 AKI defined as: A double of baseline serum creatinine from baseline OR 12 hours of urine output of less than 0.5ml/kg/hr in those with bladder catheters. If no catheter in place than urine output based AKI cannot be diagnosed	Within 7 days of enrollment

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Development of KDIGO stage 3 AKI	Number of patients developing KDIGO Stage 3 AKI KDIGO Stage 3 AKI defined as: Increase in Serum creatinine by 3.0 times baseline OR Increase serum creatinine to > 4.0 mg/dL OR Need for Renal Replacement Therapy (RRT)	within 12 hour of each observation, within 7 days of enrollment and 90 day MAKE outcome
Recipient of renal replacement therapy(RRT)	The number of patients who receive RRT	within 7 days of enrollment and 90 day make outcome
Clinical indication for the receipt of renal replacement therapy(RRT)	The number of patients who have a clinical indication to receive RRT (even if they do not receive it) due to following indications (in the setting of Stage 2/3 AKI): Hyperkalemia (≥ 6 mmol/L); Diuretic-resistant hypervolemia (difficult to define); BUN urea serum levels greater than or equal to 150mg/ dL; Severe metabolic acidosis (pH ≤ 7.15); Oliguria (urinary output < 200mL/12hr), or anuria.	within 12 hour of each observation, within 7 days of enrollment and 90 day make outcome
Change in Mortality Status during hospitalization	Patients' mortality status during current hospitalization	within 12 hour of each observation, within 7 days of enrollment and during current hospitalization
Major Adverse Kidney Events (MAKE) Outcomes	Number of Participants developing Major Adverse Kidney Events (MAKE): Recurrent Hospitalization; Kidney Function Status:Recurrent AKINew chronic kidney disease (CKD)Need or continued need for RRT; Mortality	3 months (90 days)

Collaborators and Investigators

• Sponsor: University of Chicago
• Collaborators: National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK); University of Wisconsin, Madison
• Investigators: Principal Investigator: Jay Koyner, MD, University of Chicago; Principal Investigator: Matthew Churpek, MD,MPH,PhD, University of Wisconsin, Madison

Publications and helpful links

General Publications

• Koyner JL, Martin J, Carey KA, Caskey J, Edelson DP, Mayampurath A, Dligach D, Afshar M, Churpek MM. Multicenter Development and Validation of a Multimodal Deep Learning Model to Predict Moderate to Severe AKI. Clin J Am Soc Nephrol. 2025 Apr 15;20(6):766-778. doi: 10.2215/CJN.0000000695.

Study record dates

Study Major Dates

• Study Start (Actual): January 5, 2024
• Primary Completion (Estimated): March 1, 2027
• Study Completion (Estimated): March 1, 2028

Study Registration Dates

• First Submitted: August 4, 2023
• First Submitted That Met QC Criteria: August 4, 2023
• First Posted (Actual): August 14, 2023

Study Record Updates

• Last Update Posted (Estimated): September 12, 2025
• Last Update Submitted That Met QC Criteria: September 5, 2025
• Last Verified: September 1, 2025

More Information

Terms related to this study

• Keywords: Biomarkers; Artificial Intelligence; Risk Assessment; Acute Kidney Injury; Renal Replacement Therapy; Clinical Nephrology
• Additional Relevant MeSH Terms: Urogenital Diseases; Male Urogenital Diseases; Kidney Diseases; Urologic Diseases; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Renal Insufficiency; Acute Kidney Injury
• Other Study ID Numbers: IRB23-0343; R01DK126933 (U.S. NIH Grant/Contract)

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No