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Longitudinal HbA1c trajectories and clinical prognosis in type 2 diabetes: a population-based cohort study
Jose A Quesada1,2, Francisco Jose Pomares-Gomez3,4, Amanda Esquerdo-Arroyo2,3,5
1Cardiovascular Research Group (GRINCAVA), Clinical Medicine Department, School of Medicine, Miguel Hernandez University of Elche (UMH), Crta. Nacional N-332 s/n, 03550 Sant Joan d'Alacant, Spain.
Objective:
To characterize longitudinal glycated haemoglobin (HbA1c) trajectories before and after the diagnosis of type 2 diabetes and to evaluate their association with major cardiovascular events and all-cause mortality.
Design:
Retrospective population-based cohort study using Spanish electronic health records. Adults with incident type 2 diabetes diagnosed between 2005 and 2019 were included. Longitudinal HbA1c trajectories were modelled using functional principal component analysis and classified using Gaussian mixture modelling. The primary outcome was a composite of hospital admission for ischaemic heart disease, cerebrovascular disease, and all-cause mortality. Associations were assessed using adjusted Cox proportional hazards models.
Results:
A total of 264 634 individuals with incident type 2 diabetes and 1 719 720 HbA1c measurements were included. Three distinct HbA1c trajectory classes were identified. Mean HbA1c values remained within the prediabetes range until ~10 years before diabetes diagnosis. The highest risk of the composite outcome was observed in the trajectory class with intermediate, rather than the highest, HbA1c levels. Compared with trajectory class 2, trajectory class 1 was associated with a substantially increased risk of the composite outcome in women (HR: 3.34, 95% CI: 3.18-3.50) and men (HR: 2.93, 95% CI: 2.81-3.05).
Conclusions:
The trajectory associated with the greatest risk was not the one with the highest HbA1c levels, but the one characterized by greater baseline clinical vulnerability. The greatest impact of the associations falls on total mortality. These findings highlight the importance of considering long-term glycaemic patterns alongside clinical context when stratifying cardiovascular risk in people with type 2 diabetes.
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