Back to search

Article

Prediabetes Phenotype Clusters in the Diabetes Prevention Program Study

2024-12-05

Abstract excerpt

<h4>ABSTRACT</h4> <h4>Objective</h4> The purpose of this study was to apply clustering methods to identify and characterize prediabetes phenotypes and their relationships with treatment arm and type 2 diabetes (T2D) outcomes in the Diabetes Prevention Program (DPP), and to compare the utility of additional clustering measures in phenotype characterization and T2D risk stratification. <h4>Research Design and Meth...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
107dfa30-c137-506b-aad6-fa202c7bc463
DOI
10.1101/2024.12.02.626435
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Prediabetes Phenotype Clusters in the Diabetes Prevention Program StudyDOI 10.1101/2024.12.02.626435
Body Composition Differentiates Prediabetes Phenotype Clusters in the Diabetes Prevention Program Study.Semantic proximity
Novel subgroups of prediabetes and the associations with outcomes in health professionals: a data–driven cluster analysisSemantic proximity
Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals: An IMI DIRECT study.Semantic proximity
Clustering of adult-onset diabetes into novel subgroups guides therapy and improves prediction of outcomeSemantic proximity
Type 1 Diabetes Risk Phenotypes Using Cluster AnalysisSemantic proximity
Cardiorenal Risk Profiles Among Data-Driven Type 2 Diabetes Sub-Phenotypes: A Post-Hoc Analysis of the China Health and Nutrition Survey.Semantic proximity
An Integrative Approach for Identification of Pre-Diabetes Clusters and Glycaemic Prediction using Ensemble Machine LearningSemantic proximity
Type 2 Diabetes Sub-Phenotypes and Their Association with Cardiovascular Disease Risk: A Multi-Center StudySemantic proximity
Comparison of clustering and phenotyping approaches for subclassification of type 2 diabetes and its association with remission in Indian population.Semantic proximity
Characterizing the weight-glycemia phenotypes of type 1 diabetes in youth and young adulthood.Semantic proximity
Genetic Subtypes of Prediabetes, Healthy Lifestyle, and Risk of Type 2 Diabetes.Semantic proximity
Cluster Analysis of Cardiovascular Phenotypes in Patients With Type 2 Diabetes and Established Atherosclerotic Cardiovascular Disease: A Potential Approach to Precision Medicine.Semantic proximity
Select a neighboring publication to make it the new centre.