Hypertension
Hypertension is a chronic disease characterized by persistently elevated blood pressure and is a major vascular risk factor associated with cardiovascular disease, stroke, heart failure, and chronic kidney disease.
Hypertension is a chronic disease characterized by persistently elevated blood pressure and is a major vascular risk factor associated with cardiovascular disease, stroke, heart failure, and chronic kidney disease. Its clinical importance reflects its relationship with multiple organ systems: hypertension is studied alongside diabetes, obesity, dyslipidemia, smoking, renal function, proteinuria, and other determinants of cardiovascular and cardio-renal risk.
Management commonly involves blood-pressure monitoring, lifestyle measures, and antihypertensive medication. Some patients remain above treatment targets despite therapy; the EnligHTN study specifically examined patients who began a third antihypertensive class while continuing a stable two-drug regimen, representing a population with more difficult-to-control hypertension 42726373Sep. Current research also evaluates hypertension through care cascades, treatment patterns, population disparities, genetic risk, and its relationships with heart failure, type 2 diabetes, brain white-matter microstructure, and mortality.
- Machine learning and deep learning-based prediction of hypertension and analysis of its major risk factors in Bangladesh. PMID 42752631
Where the papers sit
12 papers study hypertension directly. The themes below are drawn from those 12.
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Cardiometabolic Risk and Outcomes : Cardiometabolic risk assessment is broadening beyond conventional factors to polygenic scores, vascular measures, self-reported disease history and DASH diet adherence. Sex-specific trajectories and links to heart failure, mental health and white-matter integrity recur, but no single intervention dominates. 5 papers · 41.7%
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Hypertension Care and Treatment : Care gaps persist across hypertension management, from difficult-to-control medication regimens to rural and HIV-related losses in the care cascade. Primary-care work also examines sex differences in physician-patient management, but no single treatment strategy dominates. 4 papers · 33.3%
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Machine Learning for Cardiometabolic Risk : Machine-learning models are moving from hypertension prediction toward social and metabolic risk stratification across diabetes, obesity and cardiovascular disease. Recurring priorities are sensitivity, major-risk-factor discovery and validation across regions and multi-ethnic populations, not treatment selection. 3 papers · 25%
Recent Findings on hypertension
Cardiometabolic Risk and Outcomes: Hypertension was the most frequent event after type 2 diabetes onset across age groups and sexes, while men more often developed cardiovascular disease or end-stage renal disease and women more often developed mental health conditions 42640878Aug. Greater DASH adherence was associated with lower risks of heart failure, heart failure-related death, hypertension, and type 2 diabetes 42575672Aug. Hypertension and heart disease showed the most robust, widespread associations with white matter microstructure, whereas diabetes associations weakened and body mass index findings remained inconsistent 42535262Jul. Self-reported hypertension had high specificity but only 69.9% sensitivity, with reporting accuracy influenced by healthcare engagement and time since diagnosis or hospital care 42576717Aug. Integrated polygenic risk scores improved cardiovascular risk classification, including for hypertension, although broader prospective validation is still needed to establish clinical utility 42053472Apr.
Hypertension Care and Treatment: Patients with harder-to-control hypertension frequently discontinued a third antihypertensive class within 12 months, and many remained above blood pressure targets 42726373Sep. Rural Medicare beneficiaries also had a high prevalence of uncontrolled hypertension, with overweight and obesity associated with higher odds; frequent physical activity showed an unexpected association with poor control 42720604Sep. People living with HIV were more likely to remain undiagnosed, lose treatment, and progress from controlled to uncontrolled blood pressure than people without HIV 42726776Sep. Physician-patient sex dyads showed variable associations with antihypertensive treatment across Swiss populations, with differences more evident among older patients 41992428Apr. These findings direct attention toward treatment persistence, integrated chronic care, rural health-system factors, and context-specific primary-care management.
Machine Learning for Cardiometabolic Risk: Machine-learning models identify different strengths in hypertension risk classification: weighted logistic regression achieved higher accuracy and specificity, whereas random forest achieved higher recall and F1-score 42752631Sep. In New York City, socioeconomic disadvantage, the built environment, and commute time explained much of the geographic variation in hypertension and diabetes prevalence 42714583Sep. A multi-ethnic model combining hypertension, diabetes, metabolic score for visceral Fat, renal markers, and age classified prevalent cardiovascular disease in people with obesity with good internal and external discrimination 42480980Jul. Future work is emphasizing sensitivity, interpretable social-risk factors, external validation, and performance across regions and multi-ethnic populations.
Written from 12 PubMed abstracts, each one cited by PMID above. Published: 2026-09-13. Last written: 2026-09-19 by GPT. Drafted by language models from published abstracts; not medical advice.