[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100581967":3},{"organization":4,"armGroups":7,"interventions":7,"overallOfficials":8,"centralContacts":12,"locations":7,"responsibleParty":22,"collaborators":7,"id":26,"slug":27,"hasResults":28,"nctId":29,"briefTitle":30,"officialTitle":31,"acronym":7,"eligibilityCriteria":32,"healthyVolunteers":28,"sex":33,"minAge":34,"maxAge":7,"enrollmentInfo":35,"targetDuration":38,"studyType":39,"phases":7,"briefSummary":40,"conditions":41,"keywords":7,"overallStatus":44,"whyStopped":7,"lastUpdateSubmitDate":45,"lastUpdatePostDateStruct":46,"startDateStruct":49,"completionDateStruct":50,"leadSponsor":52,"locationsCount":7},{"fullName":5,"class":6},"Assiut University","OTHER",null,[9],{"name":10,"affiliation":5,"role":11},"Alaa El-Dein ElMoneim Sayed, professor","STUDY_DIRECTOR",[13,18],{"name":14,"role":15,"phone":16,"phoneExt":7,"email":17},"Kareem Sherif Mosabah, Assistant lecturer","CONTACT","+201002447880","kareemsherif14@gmail.com",{"name":19,"role":15,"phone":20,"phoneExt":7,"email":21},"Radwa Awad Abd El Hafez, lecturer","+201003797448","radwaawad@aun.edu.eg",{"type":23,"investigatorFullName":24,"investigatorTitle":25,"investigatorAffiliation":5,"oldNameTitle":7,"oldOrganization":7},"PRINCIPAL_INVESTIGATOR","Kareem Sherif","Assisstant lecturer of critical care","100581967","assessment-of-ai-prediction-models-in-prediction-of-acute-kidney-injury-in-critical-patients-100581967",false,"NCT06857188","Assessment of AI Prediction Models in Prediction of Acute Kidney Injury in Critical Patients","Role of Artificial Intelligence in the Prediction of AKI in Critically Ill Patients","Inclusion Criteria:\n\n* All adult (aged 18 years old and older) patients who were admitted to the ICU were included in this study.\n\nExclusion Criteria:\n\n* • patients under 18 years old\n\n  * End-stage renal disease\n  * Acute Kidney Injury at ICU admission\n  * Inability to obtain sufficient clinical data","ALL","18 Years",{"count":36,"type":37},1000,"ESTIMATED","1 Day","OBSERVATIONAL","The assessment of AI -based prediction models in detecting AKI early in critically ill patients. Specifically, the aim is to evaluate the model's ability to predict the onset of AKI before it clinically manifests allowing for early interventions",[42,43],"Acute Kidney Failure","Artificial Intelligence (AI)","NOT_YET_RECRUITING","2025-05-14",{"date":47,"type":48},"2025-05-16","ACTUAL",{"date":45,"type":37},{"date":51,"type":37},"2026-03-01",{"name":5,"class":6}]