Data-Driven Phenotypic Clusters of Gestational Diabetes Mellitus and Associations With Risk of Perinatal Complications and Postpartum Diabetes
Our study identified distinct data-driven GDM phenotypic clusters with differential risks of perinatal complications and postpartum diabetes. These findings may inform personalized risk assessment and management strategies tailored to GDM phenotypic clusters to possibly reduce adverse health outcomes.
Authors
- Lauren D. Liao (ORCID: https://orcid.org/0000-0003-4697-6909)
- RACHEL HARVILL
- Amanda L. Ngo (ORCID: https://orcid.org/0000-0002-4976-3469)
- Ben J Marafino
- Mara B. Greenberg
- Rana F. Chehab
- Assiamira Ferrara
- Yeyi Zhu
Institutions
- Kaiser Permanente (US)
- University of California, San Francisco (US)
- Kaiser Permanente Santa Clara Medical Center (US)
- Berkeley Public Health Division (US)
- European Automobile Manufacturers Association (BE)
- University of California, Berkeley (US)
Publication Details
- Journal
- Diabetes Care
- Published
- 2026-03-17
- DOI
- https://doi.org/10.2337/dc25-2131
- Primary Topic
- Gestational Diabetes Research and Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00