[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"trial:NCT06840210":3,"trial-entities:NCT06840210":80,"trial-summary:NCT06840210":84},{"id":4,"nct_id":4,"org_study_id":5,"brief_title":6,"official_title":7,"overall_status":8,"completion_date":9,"status_verified_date":10,"last_update_date":11,"start_date":12,"sponsor_name":13,"lead_sponsor_class":14,"has_dmc":15,"brief_summary":16,"detailed_description":17,"conditions":18,"keywords":20,"study_type":26,"primary_purpose":17,"phases":27,"enrollment_info":28,"interventions":31,"primary_outcomes":32,"secondary_outcomes":36,"sex":44,"minimum_age":45,"maximum_age":17,"healthy_volunteers":15,"eligibility_criteria":46,"std_ages":50,"locations":53,"central_contacts":69,"overall_officials":75,"references":78,"see_also_links":79},"NCT06840210","IRB00367884","Effectiveness-Implementation Evaluation of Acute Kidney Injury Decision Support","Transforming Kidney Care in the Emergency Department: A Prospective Effectiveness-Implementation Evaluation","RECRUITING","2030-12-01","2026-04","2026-04-20","2026-03-10","Johns Hopkins University","OTHER",false,"Study Purpose: This study is testing an artificial intelligence (AI)-powered clinical decision support (CDS) system designed to help emergency department (ED) doctors detect and manage acute kidney injury (AKI) earlier. The goal is to see whether the tool improves patient care, clinician decision-making, and hospital outcomes when used in real-world ED settings.\n\nStudy Design:\n\nThe AI tool will be gradually introduced at three hospital EDs:\n\nJohns Hopkins Hospital (JHH) Bayview Medical Center (BMC) Howard County General Hospital (HCGH)\n\nBefore the tool is activated, it will run in the background to collect baseline data without influencing care. Once implemented, doctors will receive training, and researchers will track how often the tool is used and whether it improves AKI care.\n\nWhat the Study Measures:\n\nProcess Outcomes: Does the tool help doctors identify AKI sooner, avoid harmful medications, and improve decision-making about hospitalization?\n\nClinical Outcomes: Does the tool reduce the number and severity of AKI cases and improve kidney-related health outcomes?\n\nImplementation Outcomes: Do ED doctors find the tool useful? Does it fit into the ED doctor's workflow without slowing the ED doctor's down?\n\nExpected Impact: If successful, the AI tool could be expanded to other hospitals and used to improve early detection and treatment of AKI, reducing kidney complications and improving patient care nationwide.",null,[19],"Acute Kidney Injury",[19,21,22,23,24,25],"AKI","Prediction","Machine Learning","Emergency Department","Clinical Decision Support","OBSERVATIONAL",[],{"count":29,"type":30},200000,"ESTIMATED",[],[33],{"measure":34,"timeFrame":35},"Number of Patients who receive Guideline-Concordant Kidney Care","From time of decision support provision until departure from the ED, approximately 6 hours",[37,40],{"measure":38,"timeFrame":39},"New or Progressive Acute Kidney Injury","Within 72 hours of first creatinine measurement in the ED",{"measure":41,"description":42,"timeFrame":43},"Perceived usefulness and usability of AKIDS software as assessed by the System Usability Score","Will be assessed using the usability using the System Usability Score, a 10-item Likert scale that yields a single composite score on a scale of 0-100, with 100 being most usable.","Prior to AKIDS implementation, immediately after implementation, and post implementation 6 months","ALL","18 Years",{"inclusion":47,"exclusion":48,"raw_text":49},[],[],"Inclusion Criteria:\n\nParticipants must meet all of the following conditions to be eligible for the study:\n\n1. Emergency Department Visit\n\n   Patients presenting to one of the three study site emergency departments (EDs):\n\n   Johns Hopkins Hospital (JHH) Bayview Medical Center (BMC) Howard County General Hospital (HCGH) Serum Creatinine Measurement\n2. At least one serum creatinine (sCr) test performed during the ED visit.\n3. Age: Adults (≥18 years old) at the time of ED visit.\n4. Follow-Up Data Available: To be included in analysis for the investigator's secondary effectiveness outcome (new or progressive AKI) patients must have repeat creatinine concentration measurement available within 72 hours\n\nExclusion Criteria:\n\n1. No ED Serum Creatinine Data: Patients who do not have a measured serum creatinine (sCr) value during the ED visit will not have decision support provided during the ED stay.\n2. Patients Discharged Without Follow-Up Data: Patients discharged from the ED who do not undergo a follow-up serum creatinine test within 72 hours will be excluded from analysis of new or progressive AKI outcome assessment.\n3. Age \\\u003C18 Years\n4. End-Stage Kidney Disease (ESKD) or Chronic Dialysis: Patients with a documented history of end-stage kidney disease (ESKD), (patients receiving chronic dialysis (hemodialysis or peritoneal dialysis) will will be excluded from analysis of new or progressive AKI outcome assessment).",[51,52],"ADULT","OLDER_ADULT",[54],{"facility":55,"status":8,"city":56,"state":57,"zip":58,"country":59,"contacts":60,"geoPoint":66},"Johns Hopkins Hospital","Baltimore","Maryland","21287","United States",[61],{"name":62,"role":63,"phone":64,"email":65},"Eili Klein, PhD","CONTACT","732-266-7732","eklein@jhmi.edu",{"lat":67,"lon":68},39.29038,-76.61219,[70,72],{"name":71,"role":63,"phone":64,"email":65},"Eili Y Klein, PhD",{"name":73,"role":63,"email":74},"Michael Ehmann, MD","mehmann1@jhmi.edu",[76],{"name":62,"affiliation":13,"role":77},"PRINCIPAL_INVESTIGATOR",[],[],{"nct_id":4,"conditions":81,"biomarkers":83},[82],"Acute Renal Failure",[],{"nct_id":4,"found":85,"summary":86,"prompt_version":96},true,{"design":87,"status":88,"heading":89,"summary":90,"follow_up":91,"word_count":92,"commitments":93,"compensation":94,"drugs_mentioned":95},"This is an observational study involving about 200,000 participants. The AI tool will first run in the background to collect data before it is actively used by doctors.","completed","Evaluating AI for Earlier Detection of Acute Kidney Injury","This study is evaluating an artificial intelligence (AI) tool designed to help emergency department (ED) doctors detect and manage acute kidney injury (AKI) earlier. The goal is to see if this tool improves patient care, doctor decision-making, and hospital outcomes in real-world ED settings. Researchers will track how often the tool is used and if it improves AKI care. You might be eligible if you are 18 or older and visit one of three specific emergency departments: Johns Hopkins Hospital, Bayview Medical Center, or Howard County General Hospital, and have a serum creatinine measurement taken. Success in this study means more patients receive kidney care that follows established guidelines.","Patients will be followed from the time the decision support is provided until they leave the ED, which is approximately 6 hours.",109,"Not specified in the trial record.","Not stated in the trial record.",[],"v2"]