ArticleScientific reports2017
Cluster analysis: a new approach for identification of underlying risk factors for coronary artery disease in essential hypertensive patients.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
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Who cites it
36 citing papers in PubMed.
- Risk stratification of ST-segment elevation myocardial infarction (STEMI) patients using machine learning based on lipid profiles.Lipids in health and disease · 2021Trial
- Clinical Phenotypes in Hypertension: A Data-Driven Approach to Risk Stratification.Hypertension (Dallas, Tex. : 1979) · 2026Article
- Geometric morphometrics based diagnostic model for Skeletal Class III patients.Communications medicine · 2026Article
- Unbiased Characterization of Atrial Fibrillation Phenotypic Architecture Provides Insight Into Genetic Liability and Clinically Relevant Outcomes.Circulation. Genomic and precision medicine · 2026Article
- Cluster Analysis of Patients With Acute Ischemic Stroke: Identifying Characteristics of Long Hospital Stays in a Comprehensive Hospital.Brain and behavior · 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
- Quality of life identification by unsupervised cluster analysis: A new approach to modelling the burden of endometriosis.PloS one · 2025Article
- Integration of two-dimensional echocardiography: A novel risk indicator for ST-segment elevation myocardial infarction.ESC heart failure · 2024Article
- Conceptually Funded Usability Evaluation of an Application for Leveraging Descriptive Data Analysis Models for Cardiovascular Research.Diagnostics (Basel, Switzerland) · 2024Article
- Unsupervised clustering identifies sub-phenotypes and reveals novel outcome predictors in patients with dialysis-requiring sepsis-associated acute kidney injury.Annals of medicine · 2023Observational
- Phenotyping of atrial fibrillation with cluster analysis and external validation.Heart (British Cardiac Society) · 2023Article
- Spectroscopic Identification of Bacteria Resistance to Antibiotics by Means of Absorption of Specific Biochemical Groups and Special Machine Learning Algorithm.Antibiotics (Basel, Switzerland) · 2023Article
- Phenomics and Robust Multiomics Data for Cardiovascular Disease Subtyping.Arteriosclerosis, thrombosis, and vascular biology · 2023Review
- Unsupervised learning to characterize patients with known coronary artery disease undergoing myocardial perfusion imaging.European journal of nuclear medicine and molecular imaging · 2023Article
- Deep Learning for Echocardiography: Introduction for Clinicians and Future Vision: State-of-the-Art Review.Life (Basel, Switzerland) · 2023Review
- Identification of Novel Metabolic Subtypes Using Multi-Trait Limited Mixed Regression in the Chinese Population.Biomedicines · 2022Article
- Arterial stiffness nomogram identification by cluster analysis: A new approach of vascular phenotype modeling.Journal of clinical hypertension (Greenwich, Conn.) · 2022Article
- Multi-Trait Genetic Analysis Reveals Clinically Interpretable Hypertension Subtypes.Circulation. Genomic and precision medicine · 2022Article
- Review
- Personalized Prediction of Kidney Function Decline and Network Analysis of the Risk Factors after Kidney Transplantation Using Nationwide Cohort Data.Journal of clinical medicine · 2022Article
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9 authors.
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Abstract
Grading of essential hypertension according to blood pressure (BP) level may not adequately reflect clinical heterogeneity of hypertensive patients. This study was carried out to explore clinical phenotypes in essential hypertensive patients using cluster analysis. This study recruited 513 hypertensive patients and evaluated BP variations with ambulatory blood pressure monitoring. Four distinct hypertension groups were identified using cluster analysis: (1) younger male smokers with relatively high BP had the most severe carotid plaque thickness but no coronary artery disease (CAD); (2) older women with relatively low diastolic BP had more diabetes; (3) non-smokers with a low systolic BP level had neither diabetes nor CAD; (4) hypertensive patients with BP reverse dipping were most likely to have CAD but had least severe carotid plaque thickness. In binary logistic analysis, reverse dipping was significantly associated with prevalence of CAD. Cluster analysis was shown to be a feasible approach for investigating the heterogeneity of essential hypertension in clinical studies. BP reverse dipping might be valuable for prediction of CAD in hypertensive patients when compared with carotid plaque thickness. However, large-scale prospective trials with more information of plaque morphology are necessary to further compare the predicative power between BP dipping pattern and carotid plaque.
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