[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"trial:NCT07217808":3,"trial-entities:NCT07217808":88,"trial-summary:NCT07217808":92},{"id":4,"nct_id":4,"org_study_id":5,"brief_title":6,"official_title":6,"overall_status":7,"completion_date":8,"status_verified_date":9,"last_update_date":10,"start_date":11,"sponsor_name":12,"lead_sponsor_class":13,"has_dmc":14,"brief_summary":15,"detailed_description":16,"conditions":17,"keywords":19,"study_type":23,"primary_purpose":24,"phases":25,"enrollment_info":27,"interventions":30,"primary_outcomes":36,"secondary_outcomes":41,"sex":42,"minimum_age":43,"maximum_age":44,"healthy_volunteers":14,"eligibility_criteria":45,"std_ages":52,"locations":55,"central_contacts":76,"overall_officials":83,"references":86,"see_also_links":87},"NCT07217808","HSR3-017-24W","Precision-Medicine Diagnostic Support in Hospitalized Veterans With Acute Kidney Injury","NOT_YET_RECRUITING","2029-06-30","2025-10","2025-10-16","2028-01-01","VA Office of Research and Development","FED",false,"Acute kidney injury (AKI) affects up to 20% of hospitalized Veterans and is strongly associated with morbidity and death. AKI is a diverse condition and timely and accurate diagnosis of the type of AKI is critical to begin appropriate therapies, especially those causes that require specific treatments beyond general supportive care. Yet, there are still significant gaps in the initial evaluation of AKI among hospitalized patients. Clinical decision support systems (CDSS) have shown promise to address these barriers, but most consist of simple alerting schemes and general care recommendations provided at a single point in time. The goal of this proposal is to develop and test the feasibility and usability of a rule-based and Artificial Intelligence-assisted precision CDSS tool (PRECISE-AKI) that can provide cognitive support to improve timely initial diagnostic evaluation of AKI.","Acute kidney injury (AKI), defined as a sudden loss of kidney function, affects up to 20% of hospitalized Veterans and is strongly associated with chronic kidney disease, poor quality of life, and death. Clinical practice guidelines recommend timely identification of the cause of AKI, but gaps remain in conducting the initial and subsequent diagnostic evaluation. Some causes of AKI also require specific treatments beyond supportive care, can be challenging to diagnose, and can require even more detailed evaluation including kidney biopsies. This clinical trial will evaluate the usability and feasibility of an Artificial Intelligence (AI)-assisted automated and comprehensive precision CDSS tool (PRECISE-AKI) to provide iterative cognitive support of general and nephrology-based providers in the diagnostic evaluation of hospitalized patients experiencing AKI within the Tennessee Valley Health Systems (TVHS). The investigators hypothesize that PRECISE-AKI will be acceptable, appropriate, and feasible to a variety of users and improve the diagnostic evaluation of hospitalized patients AKI.",[18],"Acute Kidney Injury (AKI)",[20,21,22],"Acute Kidney Injury","Decision Support Systems, Clinical","Artificial Intelligence","INTERVENTIONAL","OTHER",[26],"NA",{"count":28,"type":29},60,"ESTIMATED",[31],{"type":24,"name":32,"description":33,"armGroupLabels":34},"PRECISE-AKI Clinical Decision Support Tool","The Intervention arm will consist of Clinical Decision Diagnostic Support (CDS) provided by the PRECISE-AKI tool",[35],"PRECISION AKI Clinical Decision Support",[37],{"measure":38,"description":39,"timeFrame":40},"Rates of Appropriate Diagnostic Testing","Based on the presenting context, the investigators will compare rates of appropriate diagnostic testing between intervention and control patients among those meeting the AKI case definition","Up to 30 days",[],"ALL","18 Years",null,{"inclusion":46,"exclusion":48,"raw_text":51},[47],"Eligible providers will be those that have at least 4 weeks of inpatient ward team or consultation team activity during a 12-month period.",[49,50],"Ineligible providers will be those that have \\\u003C 4 weeks of inpatient ward team of consultative team activity during a 12 month period.","Hospitalizations with non-persistent (\\\u003C48 hours) stage 1 injury or less.","Inclusion Criteria:\n\n* Eligible providers will be those that have at least 4 weeks of inpatient ward team or consultation team activity during a 12-month period.\n* Case inclusion criteria will consist of hospitalizations that meet criteria for Kidney Disease Improving Global Outcomes Stage 2 injury or persistent Stage 1 injury seen by eligible providers.\n\nExclusion Criteria:\n\n* Ineligible providers will be those that have \\\u003C 4 weeks of inpatient ward team of consultative team activity during a 12 month period.\n* Hospitalizations with non-persistent (\\\u003C48 hours) stage 1 injury or less.",[53,54],"ADULT","OLDER_ADULT",[56],{"facility":57,"city":58,"state":59,"zip":60,"country":61,"contacts":62,"geoPoint":73},"Tennessee Valley Healthcare System Nashville Campus, Nashville, TN","Nashville","Tennessee","37212-2637","United States",[63,68,71],{"name":64,"role":65,"phone":66,"email":67},"Michele Lenoue-Newton, PhD","CONTACT","(615) 936-6728","michele.lenoue-newton@va.gov",{"name":69,"role":70},"Edward D Siew, MD MSc","PRINCIPAL_INVESTIGATOR",{"name":72,"role":70},"Michael E Matheny, MD MS MPH",{"lat":74,"lon":75},36.16589,-86.78444,[77,80],{"name":69,"role":65,"phone":78,"email":79},"(615) 343-1279","Edward.siew@va.gov",{"name":72,"role":65,"phone":81,"email":82},"(615) 936-0090","Michael.Matheny@va.gov",[84,85],{"name":69,"affiliation":57,"role":70},{"name":72,"affiliation":57,"role":70},[],[],{"nct_id":4,"conditions":89,"biomarkers":91},[90],"Acute Renal Failure",[],{"nct_id":4,"found":93,"summary":94,"prompt_version":104},true,{"design":95,"status":96,"heading":97,"summary":98,"follow_up":99,"word_count":100,"commitments":101,"compensation":102,"drugs_mentioned":103},"This is an interventional study, meaning participants will receive a specific intervention. It aims to enroll 60 participants, but the phase is not specified.","completed","PRECISE-AKI for Acute Kidney Injury in Hospitalized Veterans","This study is looking at a new tool called PRECISE-AKI Clinical Decision Support Tool to help doctors better diagnose acute kidney injury (AKI) in hospitalized Veterans. AKI is a sudden loss of kidney function that affects many Veterans and can lead to serious health problems. The PRECISE-AKI tool uses artificial intelligence (AI) to help doctors figure out the specific cause of AKI, which is important for getting the right treatment. The study wants to see if this tool helps doctors make more accurate diagnoses. You might be able to join if you are 18 or older and are a hospitalized Veteran with AKI that meets certain criteria. The study is currently unclear on its recruitment status and plans to enroll 60 participants. The main goal is to see if the tool improves how often doctors order the right tests for AKI, measured up to 30 days.","The primary outcome, appropriate diagnostic testing rates, will be measured up to 30 days.",146,"Not specified in the trial record.","Not stated in the trial record.",[32],"v2"]