[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"renal-diseases\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:renal-diseases":27},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,3,0,[8,46,77],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":14,"acronym":15,"eligibilityCriteria":16,"healthyVolunteers":11,"sex":17,"minAge":4,"maxAge":4,"enrollmentInfo":18,"targetDuration":21,"studyType":22,"phases":4,"briefSummary":23,"conditions":24,"keywords":29,"overallStatus":34,"whyStopped":4,"lastUpdateSubmitDate":35,"lastUpdatePostDateStruct":36,"startDateStruct":39,"completionDateStruct":41,"leadSponsor":43,"locationsCount":4},"100617000","machine-learning-and-artificial-intelligence-algorithms-to-optimize-the-performance-and-delivery-of-acute-dialysis-100617000",false,"NCT07312929","Machine Learning and Artificial Intelligence Algorithms to Optimize the Performance and Delivery of Acute Dialysis","SMART DIALYSIS - Scaling Machine Learning and Artificial Intelligence AlgoRithms to OpTimize the Performance and Delivery of Acute DIALYSIS.","SMART DIALYSIS","Inclusion Criteria\n\nPatients admitted to an intensive care unit (ICU) who require acute renal replacement therapy, either intermittent or continuous.\n\nExclusion Criteria\n\nReceipt of renal replacement therapy for less than 24 hours.\n\nPre-existing end-stage kidney disease.","ALL",{"count":19,"type":20},7500,"ESTIMATED","90 Days","OBSERVATIONAL","SMART DIALYSIS - Scaling Machine Learning and Artificial Intelligence AlgoRithms to OpTimize the Performance and Delivery of Acute DIALYSIS.\n\nHypothesis:\n\nCan the investigators develop and implement Machine Learning and Artificial Intelligence Algorithms into Clinical Information Systems to Optimize the Prescription, Delivery, and Performance of Acute Dialysis?\n\nObjective(s):\n\n1. Identify variables surrounding identified Key Performance Indicators that may be used by Machine Learning and Artificial Intelligence algorithms to optimize the prescription and performance of acute dialysis.\n2. Develop Machine Learning and Artificial Intelligence algorithms to help guide the prescription and delivery of acute dialysis in the development of Clinical Decision Support tools and Best Practice Advisories and create a ML\u002FAI Augmented SMART DIALYSIS Digital Dashboard.\n3. Implement and evaluate the performance of the developed Machine Learning and Artificial Intelligence algorithms on patient-centered and health economic outcomes.\n4. Validate and benchmark the performance of the evaluated Machine Learning and Artificial Intelligence algorithms across multiple jurisdictions.",[25,26,27,28],"Renal Dialysis","Renal Replacement Therapy","Renal Diseases","Quality Health Care",[30,31,32,33],"Dialysis","Articfical Inteligence","Key performance indicators","Machine Learning","NOT_YET_RECRUITING","2026-01-08",{"date":37,"type":38},"2026-01-12","ACTUAL",{"date":40,"type":20},"2026-06-01",{"date":42,"type":20},"2031-06-30",{"name":44,"class":45},"University of Alberta","OTHER",{"id":47,"slug":48,"hasResults":11,"nctId":49,"briefTitle":50,"officialTitle":51,"acronym":52,"eligibilityCriteria":53,"healthyVolunteers":54,"sex":17,"minAge":55,"maxAge":56,"enrollmentInfo":57,"targetDuration":4,"studyType":22,"phases":4,"briefSummary":59,"conditions":60,"keywords":62,"overallStatus":66,"whyStopped":4,"lastUpdateSubmitDate":67,"lastUpdatePostDateStruct":68,"startDateStruct":70,"completionDateStruct":72,"leadSponsor":74,"locationsCount":76},"100580790","new-advanced-vascular-imaging-ultrasound-protocols-100580790","NCT06841887","New Advanced Vascular Imaging Ultrasound Protocols","Unlock the Power of Resona 9 Ultrasound Machine: an Observational Study to Set-up and Test New Advanced Vascular Imaging Protocols","RESONA-SETTING","Inclusion Criteria:\n\n* Provision of informed consent prior to any study specific procedures\n* Female and\u002For male aged between 18 and 75 years\n* No previous history of kidney or cerebral disease and no pathologies that might have affected the vascular system\n\nExclusion Criteria:\n\n* Previous history of kidney or cerebral disease or pathologies that might have affected the vascular system\n* Legal incapacity, limited legal capacity, intellectual disability, uncooperative attitude or any other evidence that the subject will not be able to understand the study aims and procedures",true,"18 Years","75 Years",{"count":58,"type":20},60,"This is a single-center observational study aimed at setting up and testing new ultrasound vascular imaging protocols, conducted exclusively for research purposes. The study will perform US examinations in 60 subjects. The subjects enrolled in the study will be examined the first time and will then provide consent to be examined again in the future if needed.\n\nThe primary aim of this study is to set-up and test new advanced US protocol for the arm and cerebral blood vessels\n\nThe secondary objectives will be:\n\n* Define ranges of normality\u002Freference values of US-based parameters to be compared with pathological values.\n* Evaluate the repeatability and reproducibility of the acquired US measurements.\n* Evaluate the correlation between age and the acquired US measurements.\n* Evaluate the correlation between gender and the acquired US measurements.",[27,61],"Cerebral Disorder",[63,64,65],"ultrasound","imaging","vascular protocol","RECRUITING","2025-08-28",{"date":69,"type":38},"2025-09-05",{"date":71,"type":38},"2025-05-09",{"date":73,"type":20},"2027-03",{"name":75,"class":45},"Mario Negri Institute for Pharmacological Research",1,{"id":78,"slug":79,"hasResults":11,"nctId":80,"briefTitle":81,"officialTitle":81,"acronym":4,"eligibilityCriteria":82,"healthyVolunteers":11,"sex":17,"minAge":83,"maxAge":4,"enrollmentInfo":84,"targetDuration":86,"studyType":22,"phases":4,"briefSummary":87,"conditions":88,"keywords":4,"overallStatus":66,"whyStopped":4,"lastUpdateSubmitDate":93,"lastUpdatePostDateStruct":94,"startDateStruct":96,"completionDateStruct":98,"leadSponsor":100,"locationsCount":76},"100602124","multidisciplinary-dissection-of-renal-and-metabolic-effects-of-glyfozines-on-elderly-patients-from-molecular-aspects-to-clinical-indications-100602124","NCT07119424","Multidisciplinary Dissection of Renal and Metabolic Effects of Glyfozines on Elderly Patients: From Molecular Aspects to Clinical Indications","Inclusion Criteria:\n\n1. Participant is willing and able to give informed consent for participation in the study;\n2. Patients must be enrolled also in MED-Cli e MED-Mol studies by signing both the MED-Cli e MED-Mol informed consents.\n3. The medical product is the standard of care for the patient and has been prescribed according to clinical practice and independent of the present study;\n4. Age ≥65 years;\n5. Participant has not yet started the prescribed SGLT2i therapy;\n6. Participant has at least one clinical indication for SGLT2i use according to clinical practice guidelines.\n\nExclusion Criteria:\n\n1. Current or previous use of SGLT2i;\n2. Inability to sign the informed consent.","65 Years",{"count":85,"type":20},300,"6 Months","The project aims to study the impact of SGLT2i therapy on clinical and biochemical aspects. in elderly. The project will combine different types of data, such as clinical and biological information, and will use advanced Bayesian statistical methods to understand the relationship between risk factors and patient outcomes following treatment with SGLT2 inhibitors.",[89,90,91,27,92],"Elderly Patients (>65 Years)","Diabetes (DM)","Heart Disease","Internal Disease","2025-08-05",{"date":95,"type":38},"2025-08-13",{"date":97,"type":38},"2025-02-14",{"date":99,"type":20},"2027-02",{"name":101,"class":45},"Chiara Lanzani"]