ArticleScientific reports2020
A novel predicted model for hypertension based on a large cross-sectional study.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Predictive variables and diagnostic performance of cross-sectional models for hypertension detection: a systematic review.Frontiers in cardiovascular medicine · 2025Pooled it
- Development and validation of a hypertension risk prediction model using electronic health records data from general practices in Hampshire and Isle of Wight integrated care system.BMC cardiovascular disorders · 2026Article
- Machine learning approaches in identifying factors associated with hypertension and undiagnosed hypertension in adults in rural areas of Bangladesh.Archives of public health = Archives belges de sante publique · 2026Article
- Triglycerides and Hypertension in a Korean Population: An Individual-Level Mendelian Randomization Analysis.Nutrients · 2026Article
- A machine learning approach to predict hypertension using cross-sectional & two years follow up data from a health & demographic cohort of Assam, North East India.The Indian journal of medical research · 2025Article
- Development and Validation of a Hypertension Risk Prediction Model Based on Particle Swarm Optimization-Support Vector Machine.Bioengineering (Basel, Switzerland) · 2025Article
- A review of machine learning methods for non-invasive blood pressure estimation.Journal of clinical monitoring and computing · 2025Review
- Assessing the relationship between lipoprotein(a) levels and blood pressure among hypertensive patients beyond conventional measures. An observational study.Scientific reports · 2024Observational
- Identification of risk factors for hypertension in overweight and obese people and analysis of risk factor interactions: an R-based analysis.Frontiers in cardiovascular medicine · 2023Article
- Development and validation of a model to predict the risk of hypertension using anthropometric indicators in the Chinese population: a retrospective cohort study.American journal of translational research · 2023Article
- Establishment and evaluation of a risk-prediction model for hypertension in elderly patients with NAFLD from a health management perspective.Scientific reports · 2022Article
- Evaluating the risk of hypertension in residents in primary care in Shanghai, China with machine learning algorithms.Frontiers in public health · 2022Article
- Development and validation of prediction models for hypertension risks: A cross-sectional study based on 4,287,407 participants.Frontiers in cardiovascular medicine · 2022Article
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10 authors.
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Abstract
Hypertension is a global public health issue and leading risk for death and disability. It is urgent to search novel methods predicting hypertension. Herein, we chose 73158 samples of physical examiners in central China from June 2008 to June 2018. After strict exclusion processes, 33570 participants with hypertension and 35410 healthy controls were included. We randomly chose 70% samples as the train set and the remaining 30% as the test set. Clinical parameters including age, gender, height, weight, body mass index, triglyceride, total cholesterol, low-density lipoprotein, blood urea nitrogen, uric acid, and creatinine were significantly increased, while high-density lipoprotein was decreased in the hypertension group versus controls. Nine optimal markers were identified by a logistic regression model, and achieved AUC value of 76.52% in the train set and 75.81% in the test set for hypertension. In conclusions, this study is the first to establish predicted models for hypertension using the logistic regression model in Central China, which provide risk factors and novel prediction method to predict and prevent hypertension.
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