[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100560189":3},{"organization":4,"armGroups":7,"interventions":29,"overallOfficials":34,"centralContacts":39,"locations":47,"responsibleParty":65,"collaborators":68,"id":76,"slug":77,"hasResults":78,"nctId":79,"briefTitle":80,"officialTitle":80,"acronym":81,"eligibilityCriteria":82,"healthyVolunteers":78,"sex":83,"minAge":84,"maxAge":85,"enrollmentInfo":86,"targetDuration":10,"studyType":89,"phases":10,"briefSummary":90,"conditions":91,"keywords":96,"overallStatus":101,"whyStopped":10,"lastUpdateSubmitDate":102,"lastUpdatePostDateStruct":103,"startDateStruct":106,"completionDateStruct":107,"leadSponsor":109,"locationsCount":110},{"fullName":5,"class":6},"Universite du Quebec en Outaouais","OTHER",[8,14,18,22,25],{"label":9,"type":10,"description":11,"interventionNames":12},"type 1 diabetes",null,"This group comprises participants diagnosed with Type 1 diabetes according to self-reported data. The primary goal of comparing this group with medico-administrative records is to validate the algorithm's ability to accurately classify individuals with Type 1 diabetes, ensuring that they are correctly identified as such without being misclassified into other categories.",[13],"Other: no intervention",{"label":15,"type":10,"description":16,"interventionNames":17},"type 2 diabetes","This group includes participants diagnosed with Type 2 diabetes based on clinical data. The validation process focuses on assessing the algorithm's accuracy in identifying individuals with Type 2 diabetes, ensuring correct classification and minimizing the risk of misclassification as other diabetes phenotypes or non-diabetic.",[13],{"label":19,"type":10,"description":20,"interventionNames":21},"Latent autoimmune diabete in adults","This group consists of participants diagnosed with Latent Autoimmune Diabetes in Adults (LADA) according to self-reported data. The validation process for this group focuses on assessing the algorithm's ability to accurately identify individuals with LADA, which is often challenging due to its characteristics that overlap with both Type 1 and Type 2 diabetes. Accurate classification of LADA is crucial for improving treatment strategies and understanding its epidemiology.",[13],{"label":23,"type":10,"description":24,"interventionNames":10},"Non-diabetic","This group includes participants who, according to self-reported data from individuals, do not have any phenotypes of diabetes. The comparison of this group's data with medico-administrative records is crucial for identifying false positives and ensuring that the algorithms accurately exclude non-diabetic individuals from being misclassified as having diabetes.",{"label":26,"type":10,"description":27,"interventionNames":28},"other phenotypes","This group contains participants diagnosed with diabetes-related phenotypes other than Type 1, Type 2, or LADA, as well as those with rarer forms of the disease (based on clinical data). The validation aims to determine the algorithm's effectiveness in correctly identifying and classifying these less common phenotypes, which is critical for ensuring comprehensive and accurate diabetes classification.",[13],[30],{"type":6,"name":31,"description":32,"armGroupLabels":33,"otherNames":10},"no intervention","no intervention. this is observational study.",[19,26,9,15],[35],{"name":36,"affiliation":37,"role":38},"philippe C corsenac, Ph.D","UQO","PRINCIPAL_INVESTIGATOR",[40,44],{"name":36,"role":41,"phone":42,"phoneExt":10,"email":43},"CONTACT","(+1)4384934299","philippe.corsenac@uqo.ca",{"name":45,"role":41,"phone":10,"phoneExt":10,"email":46},"jeremie Riou, Ph.D","jeremie.riou@univ-angers.fr",[48],{"facility":49,"status":10,"city":50,"state":51,"zip":52,"country":53,"countryCode":54,"cosmosGeoPoint":55,"geoPoint":60,"contacts":61},"Philippe Corsenac","Montreal","Quebec","J8X 3X7","Canada","CA",{"type":56,"coordinates":57},"Point",[58,59],-73.58781,45.50884,{"lat":59,"lon":58},[62,64],{"name":63,"role":41,"phone":42,"phoneExt":10,"email":43},"philippe c corsenac, Ph.D",{"name":63,"role":41,"phone":10,"phoneExt":10,"email":10},{"type":38,"investigatorFullName":66,"investigatorTitle":67,"investigatorAffiliation":5,"oldNameTitle":10,"oldOrganization":10},"Corsenac Philippe","Dr in epidemiology and immunology",[69,71,73],{"name":70,"class":6},"McGill University",{"name":72,"class":6},"Centre de Recherche du Centre Hospitalier de l'Université de Montréal",{"name":74,"class":75},"University Hospital, Angers","OTHER_GOV","100560189","mapping-diabetes-in-quebec-validating-medico-administrative-algorithms-for-type-1-diabetes-type-2-diabetes-and-lada-100560189",false,"NCT06573905","Mapping Diabetes in Quebec: Validating Medico-administrative Algorithms for Type 1 Diabetes, Type 2 Diabetes and LADA","VDA","Inclusion Criteria:\n\n* Individuals diagnosed with Type 1, Type 2, or Latent Autoimmune Diabetes in Adults (LADA) based on clinical or self-reported data.\n* Participants diagnosed between 1997 and 2024.\n* Residents of Quebec with available medico-administrative records from 1997 to 2024.\n\nExclusion Criteria:\n\n* Non-residents of Quebec during the study period.","ALL","1 Year","40 Years",{"count":87,"type":88},17271,"ESTIMATED","OBSERVATIONAL","The goal of this observational study is to validate medico-administrative algorithms that classify diabetes phenotypes (Type 1, Type 2, and Latent Autoimmune Diabetes in Adults - LADA) in a population-based cohort in Quebec, including children, adolescents, and young adults up to 40 years old with diagnosed diabetes. The main questions it aims to answer are:\n\nCan these algorithms accurately distinguish between Type 1, Type 2, and LADA across different age groups? What is the prevalence and incidence of each diabetes phenotype in Quebec? Participants will have their medical and administrative data analyzed, including data on medication usage and healthcare visits, to validate the accuracy of the algorithms. The study will involve comparing these algorithm-based classifications with clinical diagnoses or self-reported data to ensure reliability.",[92,93,94,95],"Diabetes Mellitus, Type 1","Diabete Type 2","Diabetes;Adult Onset","Diabetes, Autoimmune",[97,98,99,100],"medico-administrative algorithms","cohort study","observational study","diabetes","NOT_YET_RECRUITING","2024-12-30",{"date":104,"type":105},"2025-01-01","ACTUAL",{"date":104,"type":88},{"date":108,"type":88},"2025-06-30",{"name":5,"class":6},1]