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.
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Diagnostic Accuracy Measures (Percentages)
Timeframe: Retrospective data from 1997 to 2024
Classification Counts (Number of Cases)
Timeframe: Retrospective data from 1997 to 2024
Likelihood Ratios (Unitless)
Timeframe: Retrospective data from 1997 to 2024