ArticleDiabetologia2024
Heterogeneity of glycaemic phenotypes in type 1 diabetes.
Article in Diabetologia, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Association between socioeconomic status and diabetic retinopathy in individuals with type 1 diabetes: a systematic review and meta-analysis.BMC medicine · 2025Pooled it
- Continuous glucose monitoring metrics based clustering in people living with type 1 diabetes identifies phenotypes associated with higher inflammation, metabolic dysfunction-associated steatotic liver disease risk, and lower insulin sensitivity.Diabetology & metabolic syndrome · 2026Article
- Biochemical and brain heterogeneity characterizes psychiatric and non-psychiatric illness.Nature communications · 2026Article
- Microbiome-Based Clustering Identifies Glycemic Control-Related Subtypes in Youth With Recent-Onset Type 1 Diabetes.MedComm · 2026Article
- Phenotypic heterogeneity of type 2 diabetes and risks of complications with a tree-like representation.Cardiovascular diabetology · 2026Article
- A bimodal dataset for diabetes research.Scientific data · 2026Article
- Precision phenotyping of type 2 diabetes in chinese populations using a variational autoencoder-informed tree model.Nature communications · 2026Article
- Diabetes heterogeneity beyond 3.8 years: missed risks of silent hypoglycaemia and long-term complications in the 4C study. Reply to Liu W, Deng B [letter].Diabetologia · 2026Article
- Phenotyping obesity through a two-dimensional tree structure reveals cardiometabolic heterogeneity.Cell reports. Medicine · 2025Article
- Phenotypic heterogeneity of type 2 diabetes and risks of all-cause and cause-specific mortality.Cell reports. Medicine · 2025Article
- Global challenges in diabetes research and care: which way forward? An appraisal from the EASD Global Council.Diabetologia · 2025Review
- Clinical Characteristics of Adenovirus Pneumonia in Children.Pathogens (Basel, Switzerland) · 2025Article
- Single-cell RNA sequencing technology was employed to construct a risk prediction model for genes associated with pyroptosis and ferroptosis in lung adenocarcinoma.Respiratory research · 2025Article
- Elucidating the heterogeneity of prediabetes through subphenotyping with a two-dimensional tree structure.Cell reports. Medicine · 2025Article
- Inflammatory Transformation of Skin Basal Cells as a Key Driver of Cutaneous Aging.International journal of molecular sciences · 2025Article
- Upregulated haptoglobin in classical monocytes serves as a diagnostic and immunological biomarker in myocardial infarction: a cross-sectional multi-omics study.Frontiers in immunology · 2025Article
- Mendelian randomization combined with single-cell sequencing analysis revealed prognostic genes related to myeloid cell differentiation in prostate cancer and experimental verification.Frontiers in immunology · 2025Article
- Machine Learning Algorithms Based on Time Series Pre-Clustering for Nocturnal Glucose Prediction in People with Type 1 Diabetes.Diagnostics (Basel, Switzerland) · 2024Article
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31 authors.
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Abstract
aims/hypothesisOur study aims to uncover glycaemic phenotype heterogeneity in type 1 diabetes.
methodsIn the Study of the French-speaking Society of Type 1 Diabetes (SFDT1), we characterised glycaemic heterogeneity thanks to a set of complementary metrics: HbA
resultsWe included 618 participants with type 1 diabetes (52.9% men, mean age 40.6 years [SD 14.1]). Our phenotypic tree identified seven glycaemic phenotypes. The 2D phenotypic tree comprised a main branch in the proximal region and glycaemic phenotypes in the distal areas. Dimension 1, the horizontal dimension, was positively associated with GRI (coefficient [95% CI]) (0.54 [0.52, 0.57]), HbA CONCLUSIONS/
interpretationOur study advances the current understanding of the complex glycaemic profile in people with type 1 diabetes and suggests that strategies based on isolated glycaemic metrics might not capture the complexity of the glycaemic phenotypes in real life. Relying on these phenotypes could improve patient stratification in type 1 diabetes care and personalise disease management.
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