[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100599384":3},{"organization":4,"armGroups":7,"interventions":10,"overallOfficials":12,"centralContacts":16,"locations":22,"responsibleParty":45,"collaborators":10,"id":47,"slug":48,"hasResults":49,"nctId":50,"briefTitle":51,"officialTitle":51,"acronym":52,"eligibilityCriteria":53,"healthyVolunteers":49,"sex":54,"minAge":55,"maxAge":56,"enrollmentInfo":57,"targetDuration":10,"studyType":60,"phases":10,"briefSummary":61,"conditions":62,"keywords":66,"overallStatus":71,"whyStopped":10,"lastUpdateSubmitDate":72,"lastUpdatePostDateStruct":73,"startDateStruct":76,"completionDateStruct":78,"leadSponsor":80,"locationsCount":81},{"fullName":5,"class":6},"Imperial College London","OTHER",[8],{"label":9,"type":10,"description":11,"interventionNames":10},"Patients with manifest pre-excitation",null,"Patients with a previous ECG demonstrating manifest pre-excitation, referred for an electrophysiology study as part of their clinical care",[13],{"name":14,"affiliation":5,"role":15},"Ahran Arnold, PhD","PRINCIPAL_INVESTIGATOR",[17],{"name":18,"role":19,"phone":20,"phoneExt":10,"email":21},"Keenan Saleh, MBBS","CONTACT","+442033132243","keenan.saleh10@imperial.ac.uk",[23],{"facility":24,"status":10,"city":25,"state":10,"zip":26,"country":27,"countryCode":28,"cosmosGeoPoint":29,"geoPoint":34,"contacts":35},"Imperial College Healthcare NHS Trust","London","W12 0HS","United Kingdom","UK",{"type":30,"coordinates":31},"Point",[32,33],-0.12574,51.50853,{"lat":33,"lon":32},[36,39,41,42],{"name":18,"role":19,"phone":37,"phoneExt":10,"email":38},"02033132243","k.saleh@nhs.net",{"name":14,"role":19,"phone":37,"phoneExt":10,"email":40},"ahran.arnold@imperial.ac.uk",{"name":14,"role":15,"phone":10,"phoneExt":10,"email":10},{"name":43,"role":44,"phone":10,"phoneExt":10,"email":10},"Zachary Whinnett, PhD","SUB_INVESTIGATOR",{"type":46,"investigatorFullName":10,"investigatorTitle":10,"investigatorAffiliation":10,"oldNameTitle":10,"oldOrganization":10},"SPONSOR","100599384","ai-ecg-accessory-pathway-localisation-study-100599384",false,"NCT07083791","AI-ECG Accessory Pathway Localisation Study","AAPLS","Inclusion Criteria:\n\n* Referred for EPS procedure as part of their clinical care, with a finding of pre-excitation on their ECG\n* Manifest pre-excitation on their ECG any time prior to their procedure\n* Able to give consent\n* Minimum age 13 years old\n* Maximum age 100 years old\n\nExclusion Criteria:\n\n* Unable to give consent\n* Adults \\> 100 years old\n* Children \\\u003C 13 years old\n* Patients with known location of their accessory pathway from a previous EP study","ALL","13 Years","100 Years",{"count":58,"type":59},100,"ESTIMATED","OBSERVATIONAL","This study seeks to validate the real-world accuracy of an AI-based algorithm for identifying the location of an accessory pathway from the 12-lead electrocardiogram",[63,64,65],"Accessory Pathway","Artifical Intelligence","ECG",[67,68,65,69,70],"AI-ECG","AI","Accessory pathway","Accessory pathway localisation","NOT_YET_RECRUITING","2025-07-21",{"date":74,"type":75},"2025-07-24","ACTUAL",{"date":77,"type":59},"2025-08-01",{"date":79,"type":59},"2027-03-01",{"name":5,"class":6},1]