Latent class growth mixture modeling of HbA1C trajectories identifies individuals at high risk of developing complications of type 2 diabetes mellitus in the UK Biobank
Individuals with T2D who show higher and more variable HbA1c trajectories are at increased risk of developing T2D-related complications. Early identification of patients at risk, based on factors such as age at diagnosis and previous healthcare utilization could improve patient outcomes.
Authors
- Alexandra C. Gillett (ORCID: https://orcid.org/0000-0002-5069-3197)
- Cathryn M. Lewis (ORCID: https://orcid.org/0000-0002-8249-8476)
- Jessica Tyrrell (ORCID: https://orcid.org/0000-0002-9256-6065)
- Dale Handley (ORCID: https://orcid.org/0009-0008-0944-1634)
- Renu Bala
Institutions
- South London and Maudsley NHS Foundation Trust (GB)
- University of Exeter (GB)
Publication Details
- Journal
- BMJ Open Diabetes Research & Care
- Published
- 2025-09-01
- DOI
- https://doi.org/10.1136/bmjdrc-2024-004826
- Citations
- 1
- Primary Topic
- Genetic Associations and Epidemiology
- Type
- article
- Field-Weighted Citation Impact
- 1.82
Funders
- National Institute for Health and Care Research
- Department of Health and Social Care
- King's College London
- NIHR Maudsley Biomedical Research Centre
- Medical Research Council