Acute Kidney InjuryNCT05988658
Combining Biomarkers and Electronic Risk Scores to Predict AKI in Hospitalized Patients
An observational study of Acute Kidney Injury and Biomarkers, run by University of Chicago at 2 sites in United States.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Acute Kidney Injury, Biomarkers
- What is being tested?
- ESTOP - AKI 2.0
- Type of treatment
- Medical device
- How many people
- 800 participants
- Where
- 2 sitesUnited States
- Study dates
- 5 Jan 2024to 1 Mar 2028
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
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)
Who may be able to join
- Age ≥ 18 years
- 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).
- 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)
- 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
Who cannot join
- Voluntary refusal or missing written consent of the patient / legal representative.
- Patients with a known history of end-stage renal disease on dialysis (including renal transplantation).
- Patients without a measured serum creatinine value during their inpatient stay.
- Patients with a creatinine >4.0 mg/dl at the time of admission or available in the EHR from the last 6 months
- Patients with prior episode of KDIGO defined AKI during this same hospitalization- regardless of E-STOP AKI 2.0 score
- Patients with prior renal consultation during their admission.
Show all 9Show fewer
- Patient with an E-STOP AKI 2.0 above the top 10% risk threshold more than 12 hours ago during this same hospital stay.
- Incarcerated patients
- Pregnant patients
Trial locations and contacts
2 sites in 1 country. Contact the study team or a site near you to ask about taking part.
United States2 sites, 2 recruiting
- Recruiting
University of Chicago Medical Center
Chicago, Illinois, 60637
Aiman Fatima, MBBS, 773-702-6201, aimanfatima@uchicagomedicine.org
Ola Anjorin, MBBS,DA,MPH, 773-704-3168, oanjorin@bsd.uchicago.edu
- Recruiting
University of Wisconsin Hospital
Madison, Wisconsin, 53792
Madeline Ogus, MS, 608-265-2878, mkoguss@medicine.wisc.edu
Michael Weber, 608-263-3369, mjweber@medicine.wisc.edu
About this study
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.
Read the 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.
- Conditions
- Acute Kidney Injury, Biomarkers
- Being tested
- ESTOP - AKI 2.0
- Keywords
- Acute Kidney Injury, Biomarkers, Renal Replacement Therapy, Artificial Intelligence, Risk Assessment, Clinical Nephrology
- Medical subject headings
- Acute Kidney Injury
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
ESTOP - AKI 2.0Device
Medical software as a Noninvasive medical device, which at the time of the project will not implement directly into subject/clinical care.
| Study group | Role | What they receive |
|---|---|---|
| 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 Receives: Device: ESTOP - AKI 2.0 |
What is being measured
The primary outcome is the main question the study is designed to answer.
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
Measured: Within 7 days of enrollment
Secondary outcomes (5)
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)
Measured: 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
Measured: 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.
Measured: 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
Measured: 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 AKI
- New chronic kidney disease (CKD)
- Need or continued need for RRT
- Mortality
Measured: 3 months (90 days)
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted14 Aug 2023
- Study start5 Jan 2024
- Primary completion1 Mar 2027 (estimated)
- Study completion1 Mar 2028 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Acute Kidney InjuryStudies of the same condition, open and under way.
- More trials run by University of ChicagoThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 800 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University of Chicago
- Sponsor type
- University, hospital or other
- Collaborators
- National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), University of Wisconsin, Madison
- Responsible party
- Sponsor
- Investigators
- Jay Koyner, MD, Principal investigator, University of ChicagoMatthew Churpek, MD,MPH,PhD, Principal investigator, University of Wisconsin, Madison
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05988658
- Sponsor's protocol ID
- IRB23-0343
- Other IDs
- R01DK126933
- Status last verified
- Sep 2025
- First submitted
- 4 Aug 2023
- Last updated
- 12 Sep 2025
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
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.
PubMed 40232856
Study at a glance
From the registry record, last updated by the sponsor on 12 Sep 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Combining Biomarkers and Electronic Risk Scores to Predict AKI in Hospitalized Patients
- ClinicalTrials.gov ID
- NCT05988658
- Acronym / sponsor ID
- IRB23-0343
- Conditions
- Acute Kidney Injury, Biomarkers
- Keywords
- Acute Kidney Injury, Biomarkers, Renal Replacement Therapy, Artificial Intelligence, Risk Assessment, Clinical Nephrology
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 800 participants (estimated)
- Lead sponsor
- University of ChicagoUniversity, hospital or other
- Collaborators
- National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), University of Wisconsin, Madison
- Study start
- 5 Jan 2024 (actual)
- Primary completion
- 1 Mar 2027 (estimated)
- Study completion
- 1 Mar 2028 (estimated)
- First posted
- 14 Aug 2023 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
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 design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Study cohort | – | Device: ESTOP - AKI 2.0Patients 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 |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- 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)
Key inclusion criteria (4 listed)
- Age ≥ 18 years
- 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).
- 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)
- 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
Key exclusion criteria (9 listed)
- Voluntary refusal or missing written consent of the patient / legal representative.
- Patients with a known history of end-stage renal disease on dialysis (including renal transplantation).
- Patients without a measured serum creatinine value during their inpatient stay.
- Patients with a creatinine >4.0 mg/dl at the time of admission or available in the EHR from the last 6 months
- Patients with prior episode of KDIGO defined AKI during this same hospitalization- regardless of E-STOP AKI 2.0 score
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| ESTOP - AKI 2.0Medical software as a Noninvasive medical device, which at the time of the project will not implement directly into subject/clinical care. | Device | Study cohort |
Primary outcome
Developing KDIGO stage 2 AKI
Time frame: Within 7 days of enrollment
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
5 secondary outcomes
Development of KDIGO stage 3 AKI
Time frame: within 12 hour of each observation, within 7 days of enrollment and 90 day MAKE outcome
Recipient of renal replacement therapy(RRT)
Time frame: within 7 days of enrollment and 90 day make outcome
Clinical indication for the receipt of renal replacement therapy(RRT)
Time frame: within 12 hour of each observation, within 7 days of enrollment and 90 day make outcome
Change in Mortality Status during hospitalization
Time frame: within 12 hour of each observation, within 7 days of enrollment and during current hospitalization
Major Adverse Kidney Events (MAKE) Outcomes
Time frame: 3 months (90 days)
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 12 Sep 2025.
- Derived from this study: PubMed 40232856Koyner 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.
Related trials for Acute Kidney Injury
Not yet recruiting
Vitamin C for Acute Kidney Injury in ACLF With Septic Shock: A Randomized Controlled Trial
Acute-on-Chronic Liver Failure (ACLF)
Not yet recruiting
Early Biomarker Kidney Injury Assessment After Acumen Directed Fluid Management in Cardiac Surgery
Renal Injury, Acute Kidney Injury
Recruiting
Acute Kidney Injury and Ultra-endurance Running
AKI (Acute Kidney Injury) Due to Trauma
Recruiting
WIN Ratio Analysis to Determine a Strategy of Non- Invasive SUpport for Respiratory Failure in the EmeRgency Department
Acute Hypoxic Respiratory Failure, Acute Respiratory Distress Syndrome (ARDS)
Not yet recruitingObservational study
Diastolic Shock Index for Predicting Hemodynamic Instability During Continuous Renal Replacement Therapy
Acute Kidney Injury, Hypotension (MeSH: D007022)
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Jay Koyner, MD principal investigator
University of Chicago
Matthew Churpek, MD,MPH,PhD principal investigator
University of Wisconsin, Madison
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Acute Kidney Injury and Biomarkers, run by University of Chicago at 2 sites in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 9 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 12 Sep 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Jay Koyner, MD (773-702-4842, jkoyner@uchicago.edu), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Developing KDIGO stage 2 AKI (time frame: Within 7 days of enrollment). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05988658, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 12 Sep 2025.