ArticleBMJ open2026
Retrospective population-based cohorts for assessing the performance of algorithmic diabetes classification and for quantifying the true burden of type 1, type 2 and LADA phenotypes in Quebec: a study protocol.
Article in BMJ open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06573905 (Mapping Diabetes in Quebec), which is not on this map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Mapping Diabetes in Quebec: Validating Medico-administrative Algorithms for Type 1 Diabetes, Type 2 Diabetes and LADA
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Authors and funding
6 authors.
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Abstract
introductionDiabetes affects 537 million people worldwide, with type 2 diabetes (T2D) estimated to account for most cases. Type 1 diabetes (T1D), latent autoimmune diabetes in adults (LADA) and other specific types due to other causes remain under-recognised, especially LADA, given the absence of a standardised definition. In the province of Quebec (Canada), no population-based prevalence and incidence estimates are available for all diabetes phenotypes. Current medico-administrative algorithms fail to distinguish among diabetes subtypes, limiting accurate surveillance and effective prevention and clinical strategies. METHODS AND ANALYSIS: This retrospective, longitudinal study (1997-2027) will be conducted in Quebec.Phase 1 will assess classification performance of the Corsenac ETHICS AND DISSEMINATION: The different ethics boards of partner institutions approved the feasibility of the study. The study was registered on ClinicalTrials.gov, NCT06573905. Results will be disseminated through scientific and public health channels.
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