[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100628451":3},{"organization":4,"outcomesModule":7,"designInfo":111,"detailedDescription":113,"studyPopulation":114,"armGroups":115,"interventions":110,"overallOfficials":119,"centralContacts":123,"locations":133,"responsibleParty":175,"collaborators":177,"id":184,"slug":110,"hasResults":185,"nctId":186,"briefTitle":187,"officialTitle":188,"acronym":189,"eligibilityCriteria":190,"healthyVolunteers":185,"sex":191,"minAge":192,"maxAge":110,"enrollmentInfo":193,"targetDuration":196,"studyType":197,"phases":110,"briefSummary":198,"conditions":199,"keywords":201,"overallStatus":136,"whyStopped":110,"lastUpdateSubmitDate":206,"lastUpdatePostDateStruct":207,"startDateStruct":210,"completionDateStruct":212,"leadSponsor":214,"locationsCount":215},{"fullName":5,"class":6},"Fundació Institut de Recerca de l'Hospital de la Santa Creu i Sant Pau","OTHER",{"primaryOutcomes":8,"secondaryOutcomes":13,"otherOutcomes":110},[9],{"measure":10,"description":11,"timeFrame":12},"Type 1 diabetes clusters","Differentiated groups of people with type 1 diabetes defined through the analysis of clinical, analytical, and glucometric variables.","Subgroups defined based on data from the year 2024.",[14,18,22,25,28,31,34,37,40,43,46,49,52,55,58,61,64,67,70,73,76,79,82,85,88,91,94,97,100,103,106,108],{"measure":15,"description":16,"timeFrame":17},"Cluster stability over time","Cluster stability over time determined using the Jaccard index as a reliability criterion: persistence of clusters over 1, 2, and 3 years. The Jaccard index (JI) measures the degree of similarity between two sets, regardless of the type of elements. It takes values between 0 and 1, with the latter corresponding to complete equality between both sets","2024 - 2027",{"measure":19,"description":20,"timeFrame":21},"Acute and chronic diabetes complications","Presence of acute complications (such as severe hypoglycemia) and chronic complications (such as retinopathy, nephropathy, and neuropathy) across the different clusters.","2024-2027",{"measure":23,"description":24,"timeFrame":21},"Glycemic control: mean glucose","Mean glucose reported in mg\u002FdL",{"measure":26,"description":27,"timeFrame":21},"Glycemic control: GMI (glucose management indicator)","GMI (glucose management indicator) reported in percentage (%)",{"measure":29,"description":30,"timeFrame":21},"Glycemic control: CV (coefficient of variation)","CV (coefficient of variation) reported in percentage (%)",{"measure":32,"description":33,"timeFrame":21},"Glycemic control: time in range","Time in range expressed as percentage:\n\n* % of time in glucose range 70-180 mg\u002Fdl (TIR) \\>70%\n* % of time in glucose range 70-140 mg\u002Fdl (TTIR) \\>70%\n\n  * % of time \\\u003C70 mg\u002Fdl (TBR1) \\\u003C4%\n  * % of time \\\u003C54 mg\u002Fdl (TBR2) \\\u003C1%\n  * % of time \\>180 mg\u002Fdl (TAR1) \\\u003C25%\n  * % of time \\>250 mg\u002Fdl (TAR2) \\\u003C5%",{"measure":35,"description":36,"timeFrame":21},"HbA1c","Lab or point-of-care HbA1c",{"measure":38,"description":39,"timeFrame":21},"Lipid profile","Laboratory mesured total cholesterol, triglycerids, LDL anb HDL",{"measure":41,"description":42,"timeFrame":21},"Creatinine","creatinine Laboratory measure. Units mg\u002FdL",{"measure":44,"description":45,"timeFrame":21},"Estimated glomerular filtration rate","laboratory estimated glomerular filtration rate. Units mL\u002Fmin\u002F1.73 m2",{"measure":47,"description":48,"timeFrame":21},"Albuminuria","Albuminuria, laboratory measure. Units mg\u002Fg",{"measure":50,"description":51,"timeFrame":21},"Antihypertensive treatment","Use of Antihypertensive treatment and its relationship with the clusters.",{"measure":53,"description":54,"timeFrame":21},"Hypolipemiant treatment: use","Use of hypolipemiant medication (yes\u002Fno)",{"measure":56,"description":57,"timeFrame":21},"Hypolipemiant treatment amongst clusters","Association between use of hypolipemiant treatment and the clusters.",{"measure":59,"description":60,"timeFrame":21},"Insulin treatment: type","Type of insulin therapy: multiple daily injections, continuous subcutaneous insulin infusion systems, hybrid closed-loop systems",{"measure":62,"description":63,"timeFrame":21},"Insulin treatment: association with the clusters","Association with the type of insulin therapy and the clusters",{"measure":65,"description":66,"timeFrame":21},"Anthropometric variables: weight","Weight in kilograms and its relationship with the clusters. Weight and height will be combined to report BMI in kg\u002Fm\\^2.",{"measure":68,"description":69,"timeFrame":21},"Anthropometric variables: height","Height in centimeters and its relationship with the clusters. Weight and height will be combined to report BMI in kg\u002Fm\\^2.",{"measure":71,"description":72,"timeFrame":21},"Anthropometric variables: waist circumference","Waist circumference in centimeters and its relationship with the clusters.",{"measure":74,"description":75,"timeFrame":21},"Substance use: tobacco","Tobacco consumption and its relationship with the clusters. Tobacco use will be reported: active tobacco use, past tobacco use, never smoker, unknown.",{"measure":77,"description":78,"timeFrame":21},"Substance use: alcohol","Acohol consumption and its relationship with the clusters. Alcohol consumption will be reported as: Low risk consumption, Risk consumption (\\>10 grams of alcohol in women, \\>20g of alcohol in men), known active alcohol disorder, Passed alcohol disorder, Unknown.",{"measure":80,"description":81,"timeFrame":21},"Age at diagnosis","Patient age at diabetes diagnosis and its relationship with the clusters.",{"measure":83,"description":84,"timeFrame":21},"Disease duration","Diabetes duration and its relationship with the clusters.",{"measure":86,"description":87,"timeFrame":21},"Pregnancy","Active pregnancy and its relationship with the clusters.",{"measure":89,"description":90,"timeFrame":21},"Parity status in women","Parity status in women and its relationship with the clusters.",{"measure":92,"description":93,"timeFrame":21},"Menstrual cycle phase","Menstrual cycle phase and its relationship with the clusters.",{"measure":95,"description":96,"timeFrame":21},"Reproductive stage in women","Reproductive stage in women and its relationship with the clusters. Reproductive stage will be reported as: Reproductive, Perimenopausal, Postmenopausal, Unknown",{"measure":98,"description":99,"timeFrame":21},"Patient-reported variables","Patient-reported health-related quality of life will be assessed using a validated questionnaire for patients with type 1 diabetes. The Spanish version of the Diabetes Quality of Life questionnaire (EsDQOL) will be used. The score obtained from the questionnaire ranges from 0 to 100, where 0 represents the lowest possible quality of life and 100 the highest possible.",{"measure":101,"description":102,"timeFrame":21},"Patient-reported variables and its association with the clusters","Correlation between patient reported health-related quality of life and the association with the clusters.",{"measure":104,"description":105,"timeFrame":21},"Sociodemographic variables","Date of birth",{"measure":104,"description":107,"timeFrame":21},"Sex assigned at birth",{"measure":104,"description":109,"timeFrame":21},"Race\u002Fethnic background reported as: White, Mediterranean or Hispanic, African or Caribbean, South Asian (Indian, Pakistani, Bangladeshi, or other Asian), East or Southeast Asian (Chinese, Japanese, or Southeast Asian), Arab or North African (including Egyptian), Unknown",null,{"allocation":110,"interventionModel":110,"interventionModelDescription":110,"primaryPurpose":110,"observationalModel":112,"timePerspective":6,"maskingInfo":110},"CASE_ONLY","Study Description\n\nMain Objective The primary objective of this study is to characterize subgroups of individuals with type 1 diabetes (T1D) based on clinical and glucometric features using an artificial intelligence (AI) approach.\n\nSecondary objectives Evaluate cluster stability over time (1, 2, and 3 years); assess cluster utility for predicting complications; analyze the contribution of different clinical variables to cluster characterization and its evolution over time; and model endpoints such as diabetes-related complications.\n\nStudy Design This is an ambispective observational study.\n\nDisease Under Study Type 1 Diabetes Mellitus.\n\nMethodology This ambispective observational study will use information extracted from participants' electronic medical records and glucometric data obtained from the corresponding monitoring platforms. The data will be analyzed using artificial intelligence techniques to identify patterns and potential subgroups within the type 1 diabetes population.\n\nStudy Population and Sample Size The study population includes individuals with type 1 diabetes (T1D) who are being followed at the Endocrinology and Nutrition Department of Hospital de la Santa Creu i Sant Pau. As this is an exploratory study, no formal sample size calculation is required. Approximately 800 patients are expected to be included.","The study population consists of individuals with type 1 diabetes (T1D) cared for at the Endocrinology and Nutrition Department of Hospital de la Santa Creu i Sant Pau.",[116],{"label":117,"type":110,"description":118,"interventionNames":110},"People with type 1 diabetes mellitus","Individuals with type 1 diabetes mellitus (T1D) cared for at the Endocrinology and Nutrition Department of Hospital de la Santa Creu i Sant Pau.",[120],{"name":121,"affiliation":5,"role":122},"Rosa M Corcoy","PRINCIPAL_INVESTIGATOR",[124,130],{"name":125,"role":126,"phone":127,"phoneExt":128,"email":129},"Eva Safont, MD","CONTACT","+34686203964","5661","esafont@santpau.cat",{"name":131,"role":126,"phone":127,"phoneExt":128,"email":132},"Rosa M Corcoy, MD, PhD","rcorcoy@santpau.cat",[134],{"facility":135,"status":136,"city":137,"state":137,"zip":138,"country":139,"countryCode":140,"cosmosGeoPoint":141,"geoPoint":146,"contacts":147},"Hospital de la Santa Creu i Sant Pau, Barcelona, Barcelona 08041","RECRUITING","Barcelona","08025","Spain","ES",{"type":142,"coordinates":143},"Point",[144,145],2.15899,41.38879,{"lat":145,"lon":144},[148,151,152,153,155,157,159,161,163,165,167,169,171,173],{"name":149,"role":126,"phone":150,"phoneExt":110,"email":132},"Rosa Corcoy, MD PhD","+34 935565661",{"name":125,"role":126,"phone":150,"phoneExt":110,"email":129},{"name":149,"role":122,"phone":110,"phoneExt":110,"email":110},{"name":125,"role":154,"phone":110,"phoneExt":110,"email":110},"SUB_INVESTIGATOR",{"name":156,"role":154,"phone":110,"phoneExt":110,"email":110},"Ana Chico, MD PhD",{"name":158,"role":154,"phone":110,"phoneExt":110,"email":110},"Alex Mesa, MD PhD",{"name":160,"role":154,"phone":110,"phoneExt":110,"email":110},"Helena Sardà, MD",{"name":162,"role":154,"phone":110,"phoneExt":110,"email":110},"Lilian C Mendoza, MD PhD",{"name":164,"role":154,"phone":110,"phoneExt":110,"email":110},"Natalia Mangas, RN",{"name":166,"role":154,"phone":110,"phoneExt":110,"email":110},"Dídac Mauricio, MD PhD",{"name":168,"role":154,"phone":110,"phoneExt":110,"email":110},"Santiago Martinez, MD",{"name":170,"role":154,"phone":110,"phoneExt":110,"email":110},"Jose M Cubero, MD PhD",{"name":172,"role":154,"phone":110,"phoneExt":110,"email":110},"Romina Miranda, PhD",{"name":174,"role":154,"phone":110,"phoneExt":110,"email":110},"Bogdan Vlacho, PhD",{"type":176,"investigatorFullName":110,"investigatorTitle":110,"investigatorAffiliation":110,"oldNameTitle":110,"oldOrganization":110},"SPONSOR",[178,181],{"name":179,"class":180},"Sociedad Española de Diabetes","NETWORK",{"name":182,"class":183},"Associació Catalana de Diabetis","UNKNOWN","100628451",false,"NCT07461805","Characterization of Type 1 Diabetes Subgroup: An Artificial Intelligence Analysis of Clinical and Glucometric Features","Caracterización de Subgrupos de Personas Con Diabetes Tipo 1: análisis de características clínicas y glucométricas Utilizando Una aproximación de Inteligencia Artificial","T1DC","Inclusion Criteria:\n\n* Individuals with type 1 diabetes (T1D) aged 18 years or older.\n* T1D individuals expected to have regular follow-up at the Endocrinology and Nutrition Department of Hospital de la Santa Creu i Sant Pau.\n* Users of continuous glucose monitoring (CGM) systems for at least the last 6 months of 2024.\n* Willingness and ability to provide written informed consent to participate in the study (by the patient or his\u002Fher representative).\n\nExclusion Criteria:\n\n* Presence of severe comorbidities or medical conditions that, in the investigator's judgment, could interfere with participation in the study or the interpretation of results. This circumstance is expected to be exceptional, as the study aims to be as inclusive as possible.","ALL","18 Years",{"count":194,"type":195},800,"ESTIMATED","4 Years","OBSERVATIONAL","The goal of this observational study is to characterize different subgroups among patients with type 1 diabetes. The main research question is:\n\nAre there distinct subtypes among people with type 1 diabetes?\n\nParticipants will be invited to take part in the study by allowing access to their health data. They will not be required to undergo any additional examinations, tests, visits, or interventions.",[200],"Type 1 Diabetes Mellitus",[202,203,204,205],"Artificial intelligence","glucometry","Clusters","Type 1 diabetes mellitus","2026-03-06",{"date":208,"type":209},"2026-03-10","ACTUAL",{"date":211,"type":209},"2025-11-04",{"date":213,"type":195},"2028-12",{"name":5,"class":6},1]