Characterization of data-driven clusters in diabetes-free adults and their utility for risk stratification of type 2 diabetes

BACKGROUND: The prevention of type 2 diabetes is challenging due to the variable effects of risk factors at an individual level. Data-driven methods could be useful to detect more homogeneous groups based on risk factor variability. The aim of this study was to derive characteristic phenotypes using...

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Detalles Bibliográficos
Autores principales: Yacamán Méndez, Diego, Zhou, Minhao, Trolle Lagerros, Ylva, Gómez Velasco, Donaji V., Tynelius, Per, Gudjonsdottir, Hrafnhildur, Ponce de Leon, Antonio, Eeg-Olofsson, Katarina, Östenson, Claes-Göran, Brynedal, Boel, Aguilar Salinas, Carlos A., Ebbevi, David, Lager, Anton
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9578256/
https://www.ncbi.nlm.nih.gov/pubmed/36253773
http://dx.doi.org/10.1186/s12916-022-02551-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9578256/
https://www.ncbi.nlm.nih.gov/pubmed/36253773
http://dx.doi.org/10.1186/s12916-022-02551-6

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