Ignite Creation Date:
2025-12-25 @ 12:37 AM
Ignite Modification Date:
2026-01-20 @ 11:19 PM
Study NCT ID:
NCT06685367
Status:
RECRUITING
Last Update Posted:
2024-11-12
First Post:
2024-10-11
Is Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
The Cost-effectiveness of Artificial Intelligence Acute Kidney Injury Prediction Auxiliary Software (Acura AKI)
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'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'RANDOMIZED', 'maskingInfo': {'masking': 'SINGLE', 'whoMasked': ['PARTICIPANT']}, 'primaryPurpose': 'PREVENTION', 'interventionModel': 'PARALLEL'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 3600}}, 'statusModule': {'overallStatus': 'RECRUITING', 'startDateStruct': {'date': '2024-10-17', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2024-11', 'completionDateStruct': {'date': '2025-09-15', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2024-11-10', 'studyFirstSubmitDate': '2024-10-11', 'studyFirstSubmitQcDate': '2024-11-10', 'lastUpdatePostDateStruct': {'date': '2024-11-12', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2024-11-12', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2025-09-15', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Acute kidney injury (AKI) incidence', 'timeFrame': 'Assessed from time of randomization to time of AKI occurrence (within 7 days post randomization)', 'description': 'Acute kidney injury (AKI) incidence in ICU. AKI is defined by an increase in KDIGO creatinine stage.'}], 'secondaryOutcomes': [{'measure': 'Percentage of recommendations implemented by the primary care team.', 'timeFrame': '24 hours after Randomization', 'description': "Upon receiving the alert message from the AI algorithm (Acura AKI), nephrologists and ICU pharmacists will review the patient's electronic health record and make treatment suggestions based on AKI bundle care protocols. They will also coordinate with the patient's primary care team to ensure that the recommendations are implemented"}, {'measure': 'Dialysis rate', 'timeFrame': 'Assessed from time of randomization to time of receipt of inpatient dialysis (within 14 days post randomization)', 'description': 'Dialysis is defined by the receipt of hemodialysis, continuous renal replacement therapy or peritoneal dialysis. Isolated ultrafiltration treatments (for the purpose of volume removal) will not be included.'}, {'measure': 'Mortality rate', 'timeFrame': 'Assessed from time of randomization to date of death from any cause, within 14 days of randomization', 'description': 'Mortality will be determined from hospital administrative records'}, {'measure': 'Length of hospital stay', 'timeFrame': 'Assessed from time of randomization to date of hospital discharge, assessed up to 30 days', 'description': 'The total days of hospitalization stay'}, {'measure': 'Change in treatment costs', 'timeFrame': 'Assessed from time of randomization to 60 days post hospital discharge date, accessed up to 90 days', 'description': '1. Hospital Services \\[Room and board (inpatient stays), Intensive care unit (ICU) fees, Emergency department charges, Operating room fees, and Recovery room fees\\]\n2. Professional Fees \\[Physician services (e.g., consultations, surgery, anesthesia), Nursing services, and Therapist services (physical, occupational, respiratory)\\]\n3. Diagnostic Services \\[Laboratory tests (blood tests, urine tests), Imaging studies (X-rays, MRI, CT scans), Biopsies, Electrocardiograms (EKGs), and Other diagnostic procedures\\]\n4. Medication and Pharmacy \\[Prescription drugs, Intravenous medications, and Anesthesia drugs\\]\n5. Medical Supplies and Equipment \\[Surgical supplies, Disposable supplies (syringes, bandages), and Prosthetics and orthotics\\]\n6. Rehabilitation Services \\[Physical therapy, Occupational therapy, Speech therapy, Cardiac rehabilitation\\]'}, {'measure': 'Long term dialysis', 'timeFrame': 'From hospital discharge date up to 90 days post discharge date', 'description': 'Receive regular dialysis'}]}, 'oversightModule': {'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Acute Kidney Injury', 'Intensive Care Units', 'Critical Ill', 'Prevention', 'Artificial Intelligence', 'Machine Learning', 'Clinical Decision Support System', 'Dialysis', 'Renal Replacement Therapy', 'Cost-effectiveness'], 'conditions': ['Acute Kidney Injury', 'Intensive Care', 'Renal Replacement Therapy']}, 'descriptionModule': {'briefSummary': '"Huede" AI Aided AKI Prediction Software, Acura AKI, uses machine learning algorithms to predict the risk of AKI within the next 24 hours and provide a ranking of feature importance. By using Acura AKI, physicians can assess the risk of AKI, focusing on high-risk patients to provide care decisions. This study will be conducted in a prospective randomized clinical trial in adult ICUs, implementing the Acura AKI system for predicting AKI. The study aims to determine whether early prediction and intervention using the Acura AKI system can improve the outcomes of critically ill patients with adverse kidney conditions. The study endpoint is to evaluate the cost-effectiveness of using Acura AKI, including the incidence of AKI, dialysis rates, mortality rates, length of hospital stay, and treatment costs.', 'detailedDescription': '"Huede" AI Aided AKI Prediction Software, Acura AKI, uses machine learning algorithms to predict the risk of AKI within the next 24 hours. It has undergone cross-hospital validation at four medical centers in Taiwan (Taichung Veterans General Hospital, Mackay Memorial Hospital, National Cheng Kung University Hospital, and Kaohsiung Medical University Hospital), successfully obtaining invention patents in Taiwan and the United States, as well as receiving a software medical device license from the Taiwan Food and Drug Administration. Acura AKI is installed on the hospital\'s servers, where it processes patient physiological data, laboratory parameters, and medication information to infer the risk of AKI occurring within 24 hours. It also provides a ranking of feature importance. By using Acura AKI, physicians can assess the risk of AKI, focusing on high-risk patients to provide care decisions.\n\nThis study will be conducted in a prospective randomized clinical trial in adult ICUs, implementing the Acura AKI system for predicting AKI. In the intervention group with Acura AKI system, physicians will be proactively notified via sending alarm message when Acura AKI identifies a high-risk patient population. After receiving alarm message, physicians and pharmacists will provide feedback and recommendations, including blood pressure, fluid management, infusion options, medication adjustment suggestions, and dialysis recommendations. The study aims to determine whether early prediction and intervention using the Acura AKI system can improve the outcomes of critically ill patients with adverse kidney conditions. Additionally, the researchers will collect 20ml of urine from Acura AKI identified patients to test for urinary biomarkers predictive of AKI then verify the performance of Acura AKI with these urinary biomarkers. The study endpoint is to evaluate the cost-effectiveness of using Acura AKI, including the incidence of AKI, dialysis rates, mortality rates, length of hospital stay, and treatment costs.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '20 Years', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Over 20 years old\n* Admitted to adult ICU\n* Hospital stay of more than 30 hours\n\nExclusion Criteria:\n\n* Known to have acute kidney injury at enrollment\n* Currently undergoing hemodialysis treatment\n* No available blood or urine test data\n* Pregnant women\n* HIV-positive patients\n* Those who have not provided informed consent form\n* Regarded as unsuitable for inclusion in the trial by the researcher'}, 'identificationModule': {'nctId': 'NCT06685367', 'briefTitle': 'The Cost-effectiveness of Artificial Intelligence Acute Kidney Injury Prediction Auxiliary Software (Acura AKI)', 'organization': {'class': 'INDUSTRY', 'fullName': 'Huede Healthtech Co., Ltd.'}, 'officialTitle': 'The Cost-effectiveness of Artificial Intelligence Acute Kidney Injury Prediction Auxiliary Software (Acura AKI)', 'orgStudyIdInfo': {'id': 'Huede-113001'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'With Acura AKI', 'description': 'The group with Acura AKI will receive the Acura AKI software, which identifies high-risk AKI patients and sends alert messages to nephrologists and ICU pharmacists. Upon receiving the alert, they will make treatment suggestions.', 'interventionNames': ['Device: Acura AKI']}, {'type': 'NO_INTERVENTION', 'label': 'Without Acura AKI', 'description': 'The group without Acura AKI will be managed based on standard medical procedures.'}], 'interventions': [{'name': 'Acura AKI', 'type': 'DEVICE', 'description': "When the AI algorithm (Acura AKI) identifies a high-risk AKI patient, nephrologists and ICU pharmacists will receive an alert message. Upon receiving the alert, they will review the patient's electronic health record and make treatment suggestions based on AKI bundle care protocols. They will also coordinate with the patient's primary care team to ensure that the recommendations are implemented", 'armGroupLabels': ['With Acura AKI']}]}, 'contactsLocationsModule': {'locations': [{'city': 'Taichung', 'status': 'RECRUITING', 'country': 'Taiwan', 'contacts': [{'name': 'Chun-Te Huang', 'role': 'CONTACT', 'email': 'huangchunte@gmail.com', 'phone': '+8864-23592525', 'phoneExt': '3169'}], 'facility': 'Taichung Veterans General Hospital (TCVGH)', 'geoPoint': {'lat': 24.1469, 'lon': 120.6839}}], 'centralContacts': [{'name': 'Chun-Te Huang', 'role': 'CONTACT', 'email': 'huangchunte@gmail.com', 'phone': '+8864-23592525', 'phoneExt': '3169'}], 'overallOfficials': [{'name': 'Chun-Te Huang', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Taichung Veterans General Hospital (TCVGH)'}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Huede Healthtech Co., Ltd.', 'class': 'INDUSTRY'}, 'responsibleParty': {'type': 'SPONSOR'}}}}