ArticleDiabetes care2022
Cluster Analysis of Cardiovascular Phenotypes in Patients With Type 2 Diabetes and Established Atherosclerotic Cardiovascular Disease: A Potential Approach to Precision Medicine.
Article in Diabetes care, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.
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Who cites it
35 citing papers in PubMed, 1 synthesis or guideline pooled it, 54 citations in OpenAlex.
- Early insulin initiation in type 2 diabetes: efficacy, safety, and clinical implications: a systematic review with narrative synthesis.Frontiers in endocrinology · 2026Pooled it
- Assessment of fatal cardiovascular disease risk using data-driven diabetes subgroups and SCORE2-Diabetes: a prospective, observational, population-based analysis of adults with diabetes in Mexico City.Lancet regional health. Americas · 2026Article
- Phenotypic clustering identifies heterogeneous cardiovascular risk among patients with elevated lipoprotein(a).Scientific reports · 2026Article
- Geometric morphometrics based diagnostic model for Skeletal Class III patients.Communications medicine · 2026Article
- Cardiometabolic Profile Segmentation in Ecuadorian University Students: A Multivariate Analysis of Lipid, Anthropometric, and Demographic Patterns.International journal of environmental research and public health · 2026Article
- Clusters of vascular aging manifestations predict incident cardiovascular events in the community.Nature communications · 2026Article
- Unsupervised cluster analysis identifies risk profiles driving heterogeneity and survival patterns in aortic aneurysm patients.Scientific reports · 2026Article
- Cardio-Oncology Risk Phenotypes in Cancer Patients Treated with Chemotherapy: A Data-Driven Analysis.Frontiers in cardiovascular medicine · 2026Article
- Unsupervised clustering identifies distinct phenotypes in acute myocardial infarction: insights from the FAST-MI 2015 registry.Frontiers in artificial intelligence · 2026Article
- A Clinical Comprehensive Evaluation of Long-Acting GLP-1 Receptor Agonists in Type 2 Diabetes Management.Diabetes, metabolic syndrome and obesity : targets and therapy · 2026Article
- Assessment of fatal cardiovascular disease risk using data-driven diabetes subgroups and SCORE2-Diabetes in 24,943 adults in Mexico City.medRxiv : the preprint server for health sciences · 2025Article
- Unsupervised machine learning for cardiovascular disease: A framework for future studies.European journal of heart failure · 2025Review
- Phenotypic heterogeneity of type 2 diabetes and risks of all-cause and cause-specific mortality.Cell reports. Medicine · 2025Article
- Article
- Quantitative DSA Analysis of MCA Aneurysms Using SymDIRECT Pixel Clustering: A Novel Framework for Objective Post-Treatment Evaluation.Diagnostics (Basel, Switzerland) · 2025Article
- Accelerated Vascular Aging as a Possible Mechanism of Troponin I Release in the Absence of Clinically Manifested Myocardial Injury.Journal of the American Heart Association · 2025Observational
- The Type III Secretion System (T3SS) of Escherichia Coli Promotes Atherosclerosis in Type 2 Diabetes Mellitus.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Vascular ageing manifestations and hypertension in the community.American journal of preventive cardiology · 2025Article
- Clinical application of cluster analysis in patients with newly diagnosed type 2 diabetes.Hormones (Athens, Greece) · 2025Article
- Cluster-Based Analysis of Lipid Profiles and Inflammation in Association With Cardiovascular Disease Incidence and Mortality: A 17.5-Year Longitudinal Study.Journal of clinical hypertension (Greenwich, Conn.) · 2025Article
Corrections and comments
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Authors and funding
17 authors at 10 institutions in 5 countries.
Funding
Abstract
objectivePhenotypic heterogeneity among patients with type 2 diabetes mellitus (T2DM) and atherosclerotic cardiovascular disease (ASCVD) is ill defined. We used cluster analysis machine-learning algorithms to identify phenotypes among trial participants with T2DM and ASCVD. RESEARCH DESIGN AND
methodsWe used data from the Trial Evaluating Cardiovascular Outcomes with Sitagliptin (TECOS) study (n = 14,671), a cardiovascular outcome safety trial comparing sitagliptin with placebo in patients with T2DM and ASCVD (median follow-up 3.0 years). Cluster analysis using 40 baseline variables was conducted, with associations between clusters and the primary composite outcome (cardiovascular death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for unstable angina) assessed by Cox proportional hazards models. We replicated the results using the Exenatide Study of Cardiovascular Event Lowering (EXSCEL) trial.
resultsFour distinct phenotypes were identified: cluster I included Caucasian men with a high prevalence of coronary artery disease; cluster II included Asian patients with a low BMI; cluster III included women with noncoronary ASCVD disease; and cluster IV included patients with heart failure and kidney dysfunction. The primary outcome occurred, respectively, in 11.6%, 8.6%, 10.3%, and 16.8% of patients in clusters I to IV. The crude difference in cardiovascular risk for the highest versus lowest risk cluster (cluster IV vs. II) was statistically significant (hazard ratio 2.74 [95% CI 2.29-3.29]). Similar phenotypes and outcomes were identified in EXSCEL.
conclusionsIn patients with T2DM and ASCVD, cluster analysis identified four clinically distinct groups. Further cardiovascular phenotyping is warranted to inform patient care and optimize clinical trial designs.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.