[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"trial:NCT05988658":3,"trial-entities:NCT05988658":129,"trial-summary:NCT05988658":133},{"id":4,"nct_id":4,"org_study_id":5,"brief_title":6,"official_title":6,"overall_status":7,"completion_date":8,"status_verified_date":9,"last_update_date":10,"start_date":11,"sponsor_name":12,"lead_sponsor_class":13,"has_dmc":14,"brief_summary":15,"detailed_description":16,"conditions":17,"keywords":20,"study_type":25,"primary_purpose":14,"phases":26,"enrollment_info":27,"interventions":30,"primary_outcomes":37,"secondary_outcomes":42,"sex":63,"minimum_age":64,"maximum_age":14,"healthy_volunteers":65,"eligibility_criteria":66,"std_ages":70,"locations":73,"central_contacts":115,"overall_officials":119,"references":123,"see_also_links":128},"NCT05988658","IRB23-0343","Combining Biomarkers and Electronic Risk Scores to Predict AKI in Hospitalized Patients","RECRUITING","2028-03-01","2025-09","2025-09-12","2024-01-05","University of Chicago","OTHER",null,"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.","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.",[18,19],"Acute Kidney Injury","Biomarkers",[18,19,21,22,23,24],"Renal Replacement Therapy","Artificial Intelligence","Risk Assessment","Clinical Nephrology","OBSERVATIONAL",[],{"count":28,"type":29},800,"ESTIMATED",[31],{"type":32,"name":33,"description":34,"armGroupLabels":35},"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\u002Fclinical care.",[36],"Study cohort",[38],{"measure":39,"description":40,"timeFrame":41},"Developing KDIGO stage 2 AKI","Number of patients developing KDIGO Stage 2 AKI.\n\nKDIGO Stage 2 AKI defined as:\n\nA double of baseline serum creatinine from baseline\n\nOR\n\n12 hours of urine output of less than 0.5ml\u002Fkg\u002Fhr in those with bladder catheters.\n\nIf no catheter in place than urine output based AKI cannot be diagnosed","Within 7 days of enrollment",[43,47,51,55,59],{"measure":44,"description":45,"timeFrame":46},"Development of KDIGO stage 3 AKI","Number of patients developing KDIGO Stage 3 AKI\n\nKDIGO Stage 3 AKI defined as:\n\nIncrease in Serum creatinine by 3.0 times baseline\n\nOR\n\nIncrease serum creatinine to \\> 4.0 mg\u002FdL\n\nOR\n\nNeed for Renal Replacement Therapy (RRT)","within 12 hour of each observation, within 7 days of enrollment and 90 day MAKE outcome",{"measure":48,"description":49,"timeFrame":50},"Recipient of renal replacement therapy(RRT)","The number of patients who receive RRT","within 7 days of enrollment and 90 day make outcome",{"measure":52,"description":53,"timeFrame":54},"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\u002F3 AKI):\n\n1. Hyperkalemia (≥ 6 mmol\u002FL)\n2. Diuretic-resistant hypervolemia (difficult to define)\n3. BUN urea serum levels greater than or equal to 150mg\u002F dL\n4. Severe metabolic acidosis (pH ≤ 7.15)\n5. Oliguria (urinary output \\\u003C 200mL\u002F12hr), or anuria.","within 12 hour of each observation, within 7 days of enrollment and 90 day make outcome",{"measure":56,"description":57,"timeFrame":58},"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",{"measure":60,"description":61,"timeFrame":62},"Major Adverse Kidney Events (MAKE) Outcomes","Number of Participants developing Major Adverse Kidney Events (MAKE):\n\n1. Recurrent Hospitalization\n2. Kidney Function Status:\n\n   * Recurrent AKI\n   * New chronic kidney disease (CKD)\n   * Need or continued need for RRT\n3. Mortality","3 months (90 days)","ALL","18 Years",false,{"inclusion":67,"exclusion":68,"raw_text":69},[],[],"Inclusion Criteria:\n\n1. Age ≥ 18 years\n2. 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).\n3. 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)\n4. 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\n\nExclusion Criteria:\n\n1. Voluntary refusal or missing written consent of the patient \u002F legal representative.\n2. Patients with a known history of end-stage renal disease on dialysis (including renal transplantation).\n3. Patients without a measured serum creatinine value during their inpatient stay.\n4. Patients with a creatinine \\>4.0 mg\u002Fdl at the time of admission or available in the EHR from the last 6 months\n5. Patients with prior episode of KDIGO defined AKI during this same hospitalization- regardless of E-STOP AKI 2.0 score\n6. Patients with prior renal consultation during their admission.\n7. Patient with an E-STOP AKI 2.0 above the top 10% risk threshold more than 12 hours ago during this same hospital stay.\n8. Incarcerated patients\n9. Pregnant patients",[71,72],"ADULT","OLDER_ADULT",[74,96],{"facility":75,"status":7,"city":76,"state":77,"zip":78,"country":79,"contacts":80,"geoPoint":93},"University of Chicago Medical Center","Chicago","Illinois","60637","United States",[81,86,90],{"name":82,"role":83,"phone":84,"email":85},"Aiman Fatima, MBBS","CONTACT","773-702-6201","aimanfatima@uchicagomedicine.org",{"name":87,"role":83,"phone":88,"email":89},"Ola Anjorin, MBBS,DA,MPH","773-704-3168","oanjorin@bsd.uchicago.edu",{"name":91,"role":92},"Jay Koyner, MD","PRINCIPAL_INVESTIGATOR",{"lat":94,"lon":95},41.85003,-87.65005,{"facility":97,"status":7,"city":98,"state":99,"zip":100,"country":79,"contacts":101,"geoPoint":112},"University of Wisconsin Hospital","Madison","Wisconsin","53792",[102,106,110],{"name":103,"role":83,"phone":104,"email":105},"Madeline Ogus, MS","608-265-2878","mkoguss@medicine.wisc.edu",{"name":107,"role":83,"phone":108,"email":109},"Michael Weber","608-263-3369","mjweber@medicine.wisc.edu",{"name":111,"role":92},"Matthew Churpek, MD,MPH,PhD",{"lat":113,"lon":114},43.07305,-89.40123,[116],{"name":91,"role":83,"phone":117,"email":118},"773-702-4842","jkoyner@uchicago.edu",[120,121],{"name":91,"affiliation":12,"role":92},{"name":111,"affiliation":122,"role":92},"University of Wisconsin, Madison",[124],{"pmid":125,"type":126,"citation":127},"40232856","DERIVED","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\u002FCJN.0000000695.",[],{"nct_id":4,"conditions":130,"biomarkers":132},[131],"Acute Renal Failure",[],{"nct_id":4,"found":134,"summary":135,"prompt_version":145},true,{"design":136,"status":137,"heading":138,"summary":139,"follow_up":140,"word_count":141,"commitments":142,"compensation":143,"drugs_mentioned":144},"This is an observational study planning to enroll 800 participants. It aims to see if adding biomarkers improves the prediction of AKI when combined with an electronic risk score.","completed","Combining Biomarkers and Electronic Risk Scores to Predict AKI","This observational study aims to improve how we predict acute kidney injury (AKI), a sudden decrease in kidney function, in hospitalized patients. Researchers are looking at whether adding information from blood and urine tests (biomarkers) can make a special computer program called ESTOP - AKI 2.0 even better at identifying patients at high risk for severe AKI. The ESTOP - AKI 2.0 program uses information from your electronic health records. The study will enroll 800 adults who are already identified as high-risk by the ESTOP - AKI 2.0 program. The main goal is to see if combining these biomarkers with the electronic risk score can more accurately predict if you will develop Stage 2 AKI within 7 days of joining the study. The current recruitment status is unclear.","The primary endpoint for developing KDIGO stage 2 AKI is measured within 7 days of enrollment.",128,"If you join, blood and urine samples will be collected over the next 3 days after you are identified as high-risk.","Not stated in the trial record.",[33],"v2"]