[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100643542":3},{"organization":4,"armGroups":7,"interventions":19,"overallOfficials":25,"centralContacts":30,"locations":18,"responsibleParty":39,"collaborators":41,"id":59,"slug":60,"hasResults":61,"nctId":62,"briefTitle":63,"officialTitle":64,"acronym":65,"eligibilityCriteria":66,"healthyVolunteers":61,"sex":67,"minAge":68,"maxAge":18,"enrollmentInfo":69,"targetDuration":18,"studyType":72,"phases":73,"briefSummary":75,"conditions":76,"keywords":80,"overallStatus":83,"whyStopped":18,"lastUpdateSubmitDate":84,"lastUpdatePostDateStruct":85,"startDateStruct":88,"completionDateStruct":90,"leadSponsor":92,"locationsCount":18},{"fullName":5,"class":6},"Queen Mary University of London","OTHER",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"AI TRIPS device intervention","EXPERIMENTAL","Patients who fit the eligibility criteria are triaged and treated at the participating trauma centre by trauma clinicians who have been exposed to the individualised risk predictions for that patient.",[13],"Device: AI-TRiPS Device",{"label":15,"type":16,"description":17,"interventionNames":18},"Usual Standard Care","NO_INTERVENTION","Patients who fit the eligibility criteria are triaged and treated at the participating trauma centre by trauma clinicians under standard conditions.",null,[20],{"type":21,"name":22,"description":23,"armGroupLabels":24,"otherNames":18},"DEVICE","AI-TRiPS Device","This is Software as a Medical Device designed to function as an aid to inform clinical situational awareness by presenting predictions of patient trajectory (probability of death, probability of trauma induced coagulopathy, probability of red cell transfusion, probability of acute kidney injury).",[9],[26],{"name":27,"affiliation":28,"role":29},"Prof. N Tai","Queen Mary University London","PRINCIPAL_INVESTIGATOR",[31,36],{"name":32,"role":33,"phone":34,"phoneExt":18,"email":35},"Dr Mays Jawad","CONTACT","+4402078827275","research.governance@qmul.ac.uk",{"name":27,"role":33,"phone":37,"phoneExt":18,"email":38},"+4402073777044","bartsheatlh.AITRIPS@nhs.net",{"type":40,"investigatorFullName":18,"investigatorTitle":18,"investigatorAffiliation":18,"oldNameTitle":18,"oldOrganization":18},"SPONSOR",[42,45,47,49,51,53,55,57],{"name":43,"class":44},"Congressionally Directed Medical Research Programs","FED",{"name":46,"class":6},"University of Aberdeen",{"name":48,"class":6},"Barts & The London NHS Trust",{"name":50,"class":6},"St George's University Hospitals NHS Foundation Trust",{"name":52,"class":6},"Imperial College Healthcare NHS Trust",{"name":54,"class":6},"King's College Hospital NHS Trust",{"name":56,"class":6},"London Ambulance Service NHS Trust",{"name":58,"class":6},"London's Air Ambulance Charity","100643542","early-phase-1-clinical-evaluation-of-an-ai-risk-prediction-system-ai-trips-100643542",false,"NCT07634185","Clinical Evaluation of an AI Risk Prediction System (AI-TRiPS)","Clinical Evaluation of an AI Risk Prediction and Decision Support System for Early Management of Injured Patients: a Stepped-wedge Cluster Randomised Trial","AI-TRiPS","Inclusion Criteria:\n\nClinician Participants\n\n* Senior clinical decision-maker involved in the initial trauma resuscitation (e.g. consultant or senior trainee in emergency medicine, anaesthesia, intensive care medicine, or surgery).\n* Based at one of the four participating Major Trauma Centres.\n* Able and willing to provide informed consent.\n* Completed the required study-specific training.\n\nTrauma Patients\n\n* Aged 16 years and above.\n* Treated and transported to a participating Major Trauma Centre by London's Air Ambulance.\n* Managed by one or more participating trauma clinicians during the resuscitation.\n\nExclusion Criteria:\n\nClinician Participants\n\n● Decline or withdraw informed consent at any stage.\n\nTrauma Patients\n\n* Aged under 16\n* Not treated by London's Air Ambulance.\n* Transported to a non-participating hospital.\n* Not managed by any participating clinicians.\n* Presenting with injuries resulting from burns, hangings, drownings, or isolated psychiatric emergencies.\n* Have registered a national NHS data opt-out or otherwise requested that their routine clinical data not be used for research.","ALL","16 Years",{"count":70,"type":71},1200,"ESTIMATED","INTERVENTIONAL",[74],"EARLY_PHASE1","The goal of this clinical study is to evaluate a software device and its impact on clinician behaviour during the initial management of trauma patients in a real-world clinical setting. Known as the AI-TRiPS Device this software uses real-time prehospital data and machine learning-based risk predictions which are displayed digitally for hospital trauma teams prior patient arrival.\n\nThe investigators will use a Stepped Wedge Cluster Randomised Controlled study design with an integrated process evaluation.\n\nThe Device will be deployed across the London Major Trauma System where the Major Trauma Centres will be the clusters. Each cluster will transition from control (standard care) to intervention at a pre-specified time (time of transition is randomised).\n\nPrimary Outcome: Clinician behaviour, assessed via the accuracy of risk prediction and clinician confidence.\n\nSecondary Outcome: Clinician acceptability, care process metrics, patient outcomes, and safety endpoints.\n\nPrimary study population: Hospital trauma clinicians, following initial resuscitation of each eligible trauma patient, who will complete electronic questionnaires.\n\nSecondary study population: Adult trauma patients, data will be collected for the duration of their index admission to hospital, to assess outcomes and enable comparison with clinician risk predictions.",[77,78,79],"Trauma","Injury","Decision Support Systems, Clinical",[81,82],"Device trial, prediction tool, trauma","clinical decision support","NOT_YET_RECRUITING","2026-06-03",{"date":86,"type":87},"2026-06-08","ACTUAL",{"date":89,"type":71},"2026-06-01",{"date":91,"type":71},"2027-12-01",{"name":5,"class":6}]