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:
Can 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.
Individuals diagnosed with Type 1, Type 2, or Latent Autoimmune Diabetes in Adults (LADA) based on clinical or self-reported data.
Participants diagnosed between 1997 and 2024.
Residents of Quebec with available medico-administrative records from 1997 to 2024.
Non-residents of Quebec during the study period.
Universite du Quebec en Outaouais
Lead sponsor
McGill University
Collaborator
Centre de Recherche du Centre Hospitalier de l'Université de Montréal
Collaborator
University Hospital, Angers
Collaborator