Ignite Creation Date:
2025-12-26 @ 10:33 AM
Ignite Modification Date:
2026-03-05 @ 1:05 AM
Study NCT ID:
NCT03590028
Status:
ACTIVE_NOT_RECRUITING
Last Update Posted:
2025-08-15
First Post:
2018-06-21
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
An Early Real-Time Electronic Health Record Risk Algorithm for the Prevention and Treatment of Acute Kidney Injury
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D058186', 'term': 'Acute Kidney Injury'}], 'ancestors': [{'id': 'D051437', 'term': 'Renal Insufficiency'}, {'id': 'D007674', 'term': 'Kidney Diseases'}, {'id': 'D014570', 'term': 'Urologic Diseases'}, {'id': 'D052776', 'term': 'Female Urogenital Diseases'}, {'id': 'D005261', 'term': 'Female Urogenital Diseases and Pregnancy Complications'}, {'id': 'D000091642', 'term': 'Urogenital Diseases'}, {'id': 'D052801', 'term': 'Male Urogenital Diseases'}]}, 'interventionBrowseModule': {'meshes': [{'id': 'D059039', 'term': 'Standard of Care'}], 'ancestors': [{'id': 'D019984', 'term': 'Quality Indicators, Health Care'}, {'id': 'D011787', 'term': 'Quality of Health Care'}, {'id': 'D006298', 'term': 'Health Services Administration'}, {'id': 'D017530', 'term': 'Health Care Quality, Access, and Evaluation'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'RANDOMIZED', 'maskingInfo': {'masking': 'NONE'}, 'primaryPurpose': 'TREATMENT', 'interventionModel': 'PARALLEL'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 180}}, 'statusModule': {'overallStatus': 'ACTIVE_NOT_RECRUITING', 'startDateStruct': {'date': '2018-10-01', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-08', 'completionDateStruct': {'date': '2026-01-31', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-08-14', 'studyFirstSubmitDate': '2018-06-21', 'studyFirstSubmitQcDate': '2018-07-05', 'lastUpdatePostDateStruct': {'date': '2025-08-15', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2018-07-18', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2024-09-06', 'type': 'ACTUAL'}}, 'outcomesModule': {'otherOutcomes': [{'measure': 'Differences by treatment group in the proportion by percent and time in days to specified medical events.', 'timeFrame': '3 months', 'description': 'The differences will be measured by treatment group in the proportion and time to event of patients who a) develop \\> Stage 2 AKI, b) require renal replacement therapy (RRT), c) undergo intensive care unit (ICU) transfer, and/or d) require non-research nephrology consult.'}, {'measure': 'Comparison of treatment groups in the proportion by percent and time in days of length of stay (LOS) in the hospital.', 'timeFrame': '3 months', 'description': 'The differences will be measured by treatment group in the proportion by percent and time in days of LOS in the hospital.'}], 'primaryOutcomes': [{'measure': 'Peak change in milligrams per deciliter (mg/dL) in serum creatinine (SCr) level over a 7-day interval', 'timeFrame': '7-day interval', 'description': 'The primary endpoint of interest, change in serum creatinine (SCr), is the peak change from study entry in SCr level over a 7-day interval. The change in SCr is defined as the maximal change in creatinine over this interval, and aim to detect a clinical difference in change in SCr between the SOC and ENC treatment groups.'}]}, 'oversightModule': {'oversightHasDmc': True, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Acute Kidney Injury']}, 'referencesModule': {'references': [{'pmid': '40232856', 'type': 'DERIVED', 'citation': '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.'}]}, 'descriptionModule': {'briefSummary': 'This is a single center randomized trial that seeks to determine if the use of an automated real-time electronic medical record Acute Kidney Injury (AKI) risk score can improve patient outcomes through the use of an early standardized nephrology focused intervention.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n1. Age \\>18 years old\n2. Initial ESTOP AKI score ≥0.01 within the last 8 hours.\n\nExclusion Criteria:\n\n1. Voluntary refusal or missing written consent of the patient / 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/dl at the time of admission or available in the electronic health record (EHR) from the last 6 months.\n5. Patients with prior episode of Kidney Disease Improving Global Outcomes (KDIGO) defined AKI during this same hospitalization- regardless of ESTOP AKI score.\n6. Patients with prior renal consultation during their admission.'}, 'identificationModule': {'nctId': 'NCT03590028', 'acronym': 'ESTOP-AKI', 'briefTitle': 'An Early Real-Time Electronic Health Record Risk Algorithm for the Prevention and Treatment of Acute Kidney Injury', 'organization': {'class': 'OTHER', 'fullName': 'University of Chicago'}, 'officialTitle': 'An Early Real-Time Electronic Health Record Risk Algorithm for the Prevention and Treatment of Acute Kidney Injury: A Randomized Trial of an Early Standardized, Personalized Nephrology Intervention', 'orgStudyIdInfo': {'id': 'IRB17-1081'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'Early Nephrology Consult (ENC)', 'description': 'The ENC will be a structured consultative note that will provide detailed recommendations around issues such as Differential Diagnosis, Drug Dosing and Volume Status. The research ENC will have a daily follow-up with documented recommendations.', 'interventionNames': ['Other: Early Nephrology Consult (ENC)']}, {'type': 'ACTIVE_COMPARATOR', 'label': 'Standard of Care (SOC)', 'description': 'Subjects will receive nephrology consultation at the typical timepoint after symptoms of AKI appear.', 'interventionNames': ['Other: Standard of Care (SOC)']}], 'interventions': [{'name': 'Early Nephrology Consult (ENC)', 'type': 'OTHER', 'description': 'The electronic risk prediction algorithm (ESTOP-AKI) will interface with electronic medical data to determine the likelihood for the patient to develop AKI. Early Nephrology Consult (ENC) will be implemented. A nephrologist will assess the subject and consult with their care team to advise a treatment plan during the hospitalization.', 'armGroupLabels': ['Early Nephrology Consult (ENC)']}, {'name': 'Standard of Care (SOC)', 'type': 'OTHER', 'description': 'Subjects will receive nephrology consultation at the typical timepoint after symptoms of AKI appear.', 'armGroupLabels': ['Standard of Care (SOC)']}]}, 'contactsLocationsModule': {'locations': [{'zip': '60637', 'city': 'Chicago', 'state': 'Illinois', 'country': 'United States', 'facility': 'University of Chicago Medical Center', 'geoPoint': {'lat': 41.85003, 'lon': -87.65005}}], 'overallOfficials': [{'name': 'Jay Koyner, MD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'University of Chicago Medicine'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'University of Chicago', 'class': 'OTHER'}, 'responsibleParty': {'type': 'SPONSOR'}}}}