ESTOP - AKI 2.0
DeviceMedical software as a Noninvasive medical device, which at the time of the project will not implement directly into subject/clinical care.
NCT Number: NCT05988658
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.
Interested in participating?
Request Info18 year and older
All sexes
Observational
University of Chicago Medical Center, Chicago, Illinois, United States
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.
Healthy volunteers accepted: No
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
Medical software as a Noninvasive medical device, which at the time of the project will not implement directly into subject/clinical care.
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
Time frame: within 12 hour of each observation, within 7 days of enrollment and 90 day MAKE outcome
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)
Time frame: within 7 days of enrollment and 90 day make outcome
The number of patients who receive RRT
Time frame: within 12 hour of each observation, within 7 days of enrollment and 90 day make outcome
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):
Time frame: within 12 hour of each observation, within 7 days of enrollment and during current hospitalization
Patients' mortality status during current hospitalization
Time frame: 3 months (90 days)
Number of Participants developing Major Adverse Kidney Events (MAKE):
Contact information is provided by the study sponsor or research team.
University of Chicago
Other
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View the official ClinicalTrials.gov record (opens in a new tab)This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.
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