[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100474687":3},{"organization":4,"armGroups":7,"interventions":10,"overallOfficials":10,"centralContacts":12,"locations":10,"responsibleParty":22,"collaborators":24,"id":27,"slug":28,"hasResults":29,"nctId":30,"briefTitle":31,"officialTitle":32,"acronym":10,"eligibilityCriteria":33,"healthyVolunteers":34,"sex":35,"minAge":36,"maxAge":10,"enrollmentInfo":37,"targetDuration":10,"studyType":40,"phases":10,"briefSummary":41,"conditions":42,"keywords":44,"overallStatus":46,"whyStopped":10,"lastUpdateSubmitDate":47,"lastUpdatePostDateStruct":48,"startDateStruct":51,"completionDateStruct":53,"leadSponsor":55,"locationsCount":10},{"fullName":5,"class":6},"University Hospitals Coventry and Warwickshire NHS Trust","OTHER",[8],{"label":9,"type":10,"description":11,"interventionNames":10},"Type1diabetes patients",null,"Males and females diagnosed with T1D, aged over 18 years old who are currently under the care of the Warwickshire Institute for the Study of Diabetes, Endocrinolgy and Metabolism (WISDEM) at the University Hospitals Coventry and Warwickshire.",[13,18],{"name":14,"role":15,"phone":16,"phoneExt":10,"email":17},"John G Hattersley, PhD","CONTACT","+44 (0) 24 7696 6068","john.hattersley@uhcw.nhs.uk",{"name":19,"role":15,"phone":20,"phoneExt":10,"email":21},"Leandro Pechhia, PhD","+44 (0) 24 7657 3383","L.Pecchia@warwick.ac.uk",{"type":23,"investigatorFullName":10,"investigatorTitle":10,"investigatorAffiliation":10,"oldNameTitle":10,"oldOrganization":10},"SPONSOR",[25],{"name":26,"class":6},"University of Warwick","100474687","ai-models-for-non-invasive-glycaemic-event-detection-using-ecg-in-type-1-diabetics-100474687",false,"NCT05461144","AI Models for Non-invasive Glycaemic Event Detection Using ECG in Type 1 Diabetics","Development and Validation of Artificial Intelligence Models for Non-invasive Glycaemic Event Detection Using ECG in Type 1 Diabetics","Inclusion Criteria:\n\nThe study will be open to all individuals living independently, over 18 years without acute illness or ongoing clinical investigation, or volunteers with a stable medical condition may be included. Volunteers with an ongoing medical condition will only be included after detailed consultation with our clinical and dietetics members of the team; however, it is imperative that volunteers are able to provide written informed consent.\n\nExclusion Criteria:\n\nWhilst the study employs a deliberately open inclusion criterion, the following exclusion measures will be employed:\n\n* Children (under 18 yrs)\n* Any adult who lacks decisional capacity\n* Claustrophobia, isolophobia, recent abnormal exercise, radiation exposure within the preceding 24 hours of entering the whole-body calorimeter and feeling unwell in any way.\n* Needle phobia\n* Any medical\u002Fendocrine problem that could affect energy expenditure (e.g. thyroid problems, Cushing's syndrome)\n* Chronic inflammatory disorders like rheumatoid arthritis, or long term use of steroids or other immunomodulators like cyclosporine, azathioprine.\n* Beta blockers\n* Currently actively losing weight\n* Depression or any psychiatric illness",true,"ALL","18 Years",{"count":38,"type":39},30,"ESTIMATED","OBSERVATIONAL","This observational study aims to recruit up to thirty T1DM patients from a diabetic outpatient clinic at the University Hospital Coventry and Warwickshire for a two-phase study. The first phase involves attending an inpatient protocol for up to thirty-six hours in a calorimetry room at the Human Metabolism Research Unit under controlled conditions, followed by a phase of free-living, for up to three days, in which participants will go about their normal daily activities without restriction. Throughout the study, the participants will wear commercially available wearable sensors to measure and record physiological signals (e.g., electrocardiogram and continuous glucose monitor). Data collected will be used to develop and validate an AI model using state-of-the-art deep-learning methods for the purpose of non-invasive glycaemic event detection.",[43],"Metabolic Disease",[45],"Endochrine","NOT_YET_RECRUITING","2022-07-12",{"date":49,"type":50},"2022-07-15","ACTUAL",{"date":52,"type":39},"2022-09-30",{"date":54,"type":39},"2027-05-01",{"name":5,"class":6}]