[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100576911":3},{"organization":4,"armGroups":7,"interventions":18,"overallOfficials":10,"centralContacts":23,"locations":29,"responsibleParty":47,"collaborators":10,"id":52,"slug":53,"hasResults":54,"nctId":55,"briefTitle":56,"officialTitle":57,"acronym":10,"eligibilityCriteria":58,"healthyVolunteers":54,"sex":59,"minAge":60,"maxAge":61,"enrollmentInfo":62,"targetDuration":10,"studyType":65,"phases":10,"briefSummary":66,"conditions":67,"keywords":69,"overallStatus":32,"whyStopped":10,"lastUpdateSubmitDate":71,"lastUpdatePostDateStruct":72,"startDateStruct":75,"completionDateStruct":77,"leadSponsor":79,"locationsCount":80},{"fullName":5,"class":6},"The Eye Hospital of Wenzhou Medical University","OTHER",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"High Risk Group",null,"Participants predicted to have a high risk of mortality based on AI-assisted prediction models using their EHR data, including medical history, lab results, dialysis treatment details, and clinical observations.",[13],"Other: AI-assisted Predictive Model for Dialysis Outcomes",{"label":15,"type":10,"description":16,"interventionNames":17},"Low Risk Group","Participants predicted to have a low risk of mortality based on the AI-assisted prediction model, who will be compared with the high-risk group for evaluating the effectiveness of early intervention strategies.",[13],[19],{"type":6,"name":20,"description":21,"armGroupLabels":22,"otherNames":10},"AI-assisted Predictive Model for Dialysis Outcomes","This study utilizes an AI-assisted predictive model that analyzes multimodal data from electronic health records, including medical history, laboratory results, dialysis treatment details, and clinical observations, to predict outcomes for dialysis patients. The model employs deep learning algorithms to predict mortality risk, intermediate outcomes such as anemia, blood pressure control, nutrition, and calcium-phosphate metabolism, and helps identify early signs of deterioration. The intervention is not a direct treatment or procedure but aims to develop a tool for predicting patient outcomes and optimizing treatment strategies to improve overall health and survival rates for dialysis patients.",[9,15],[24],{"name":25,"role":26,"phone":27,"phoneExt":10,"email":28},"Fei Liu, MD","CONTACT","+86 13810512704","liufei_2359@163.com",[30],{"facility":31,"status":32,"city":33,"state":34,"zip":10,"country":35,"countryCode":36,"cosmosGeoPoint":37,"geoPoint":42,"contacts":43},"General Hospital of PLA","RECRUITING","Beijing","Beijing Municipality","China","CN",{"type":38,"coordinates":39},"Point",[40,41],116.39723,39.9075,{"lat":41,"lon":40},[44],{"name":45,"role":26,"phone":27,"phoneExt":10,"email":46},"Delong Zhao","feiliu0108@gmail.com",{"type":48,"investigatorFullName":49,"investigatorTitle":50,"investigatorAffiliation":51,"oldNameTitle":10,"oldOrganization":10},"PRINCIPAL_INVESTIGATOR","Kang Zhang","Chief Scientist","Wenzhou Medical University","100576911","ai-driven-prediction-of-dialysis-outcome-with-ehr-100576911",false,"NCT06791447","AI-Driven Prediction of Dialysis Outcome With EHR","Predicting Clinical Outcomes in Dialysis Patients Using Electronic Health Records: An AI-Based Approach","Inclusion Criteria:\n\n1. Patients who have been undergoing dialysis (either hemodialysis or peritoneal dialysis) for at least 3 months.\n2. Complete and accessible EHR data, including medical history, laboratory test results, dialysis treatment details, and clinical observations.\n3. Participants must provide informed consent for the use of their health data for research purposes.\n\nExclusion Criteria:\n\n1. Patients with incomplete or missing critical EHR data, including medical history, laboratory results, dialysis data, or treatment details necessary for the study.\n2. Patients who have been on dialysis for less than 3 months, to ensure stable data for outcome prediction.","ALL","20 Years","100 Years",{"count":63,"type":64},1000000,"ESTIMATED","OBSERVATIONAL","This is a multi-center, clinical study designed to evaluate the application and effectiveness of an AI-assisted predictive model for outcome of dialysis patients, leveraging multimodal health data.",[68],"Dialysis Patients",[68,70],"AI-Assisted Prediction","2025-04-16",{"date":73,"type":74},"2025-04-17","ACTUAL",{"date":76,"type":74},"2023-01-01",{"date":78,"type":64},"2025-05-01",{"name":5,"class":6},1]