[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100568756":3},{"organization":4,"armGroups":7,"interventions":19,"overallOfficials":25,"centralContacts":30,"locations":36,"responsibleParty":50,"collaborators":18,"id":52,"slug":53,"hasResults":54,"nctId":55,"briefTitle":56,"officialTitle":56,"acronym":18,"eligibilityCriteria":57,"healthyVolunteers":54,"sex":58,"minAge":59,"maxAge":18,"enrollmentInfo":60,"targetDuration":18,"studyType":63,"phases":64,"briefSummary":66,"conditions":67,"keywords":71,"overallStatus":38,"whyStopped":18,"lastUpdateSubmitDate":80,"lastUpdatePostDateStruct":81,"startDateStruct":84,"completionDateStruct":86,"leadSponsor":88,"locationsCount":89},{"fullName":5,"class":6},"Huede Healthtech Co., Ltd.","INDUSTRY",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"With Acura AKI","EXPERIMENTAL","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.",[13],"Device: Acura AKI",{"label":15,"type":16,"description":17,"interventionNames":18},"Without Acura AKI","NO_INTERVENTION","The group without Acura AKI will be managed based on standard medical procedures.",null,[20],{"type":21,"name":22,"description":23,"armGroupLabels":24,"otherNames":18},"DEVICE","Acura AKI","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",[9],[26],{"name":27,"affiliation":28,"role":29},"Chun-Te Huang","Taichung Veterans General Hospital (TCVGH)","PRINCIPAL_INVESTIGATOR",[31],{"name":27,"role":32,"phone":33,"phoneExt":34,"email":35},"CONTACT","+8864-23592525","3169","huangchunte@gmail.com",[37],{"facility":28,"status":38,"city":39,"state":18,"zip":18,"country":40,"countryCode":41,"cosmosGeoPoint":42,"geoPoint":47,"contacts":48},"RECRUITING","Taichung","Taiwan","TW",{"type":43,"coordinates":44},"Point",[45,46],120.6839,24.1469,{"lat":46,"lon":45},[49],{"name":27,"role":32,"phone":33,"phoneExt":34,"email":35},{"type":51,"investigatorFullName":18,"investigatorTitle":18,"investigatorAffiliation":18,"oldNameTitle":18,"oldOrganization":18},"SPONSOR","100568756","the-cost-effectiveness-of-artificial-intelligence-acute-kidney-injury-prediction-auxiliary-software-acura-aki-100568756",false,"NCT06685367","The Cost-effectiveness of Artificial Intelligence Acute Kidney Injury Prediction Auxiliary Software (Acura AKI)","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","ALL","20 Years",{"count":61,"type":62},3600,"ESTIMATED","INTERVENTIONAL",[65],"NA","\"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.",[68,69,70],"Acute Kidney Injury","Intensive Care","Renal Replacement Therapy",[68,72,73,74,75,76,77,78,70,79],"Intensive Care Units","Critical Ill","Prevention","Artificial Intelligence","Machine Learning","Clinical Decision Support System","Dialysis","Cost-effectiveness","2024-11-10",{"date":82,"type":83},"2024-11-12","ACTUAL",{"date":85,"type":83},"2024-10-17",{"date":87,"type":62},"2025-09-15",{"name":5,"class":6},1]