ArticleJournal of personalized medicine2021
Development of the Hypertension Index Model in General Adult Using the Korea National Health and Nutritional Examination Survey and the Korean Genome and Epidemiology Study.
Article in Journal of personalized medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.
- Prognostic risk models for incident hypertension: A PRISMA systematic review and meta-analysis.PloS one · 2024Pooled it
- Predicting survival factor following suicide attempt in Iran: an ensemble machine learning technique.BMC psychiatry · 2025Article
- Development of hypertension models for lung cancer screening cohorts using clinical and thoracic aorta imaging factors.Scientific reports · 2024Article
- Shapely additive values can effectively visualize pertinent covariates in machine learning when predicting hypertension.Journal of clinical hypertension (Greenwich, Conn.) · 2023Article
- Prediction Model for Pre-Eclampsia Using Gestational-Age-Specific Serum Creatinine Distribution.Biology · 2023Article
- Quantitative ultrasound for non-invasive evaluation of subclinical rejection in renal transplantation.European radiology · 2023Article
- Development of a convenient and effective hypertension risk prediction model and exploration of the relationship between Serum Ferritin and Hypertension Risk: a study based on NHANES 2017-March 2020.Frontiers in cardiovascular medicine · 2023Article
- Article
- Evaluating the risk of hypertension in residents in primary care in Shanghai, China with machine learning algorithms.Frontiers in public health · 2022Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hypertension, a risk factor for cardiovascular disease and all-cause mortality, has been increasing. Along with emphasizing awareness and control of hypertension, predicting the incidence of hypertension is important. Several studies have previously reported prediction models of hypertension. However, among the previous models for predicting hypertension, few models reflect various risk factors for hypertension. We constructed a sex-specific prediction model using Korean datasets, which included socioeconomic status, medical history, lifestyle-related variables, anthropometric status, and laboratory indices. We utilized the data from the Korea National Health and Nutrition Examination Survey from 2011 to 2015 to derive a hypertension prediction model. Participants aged 40 years or older. We constructed a sex-specific hypertension classification model using logistic regression and features obtained by literature review and statistical analysis. We constructed a sex-specific hypertension classification model including approximately 20 variables. We estimated its performance using the Korea National Health and Nutrition Examination Survey dataset from 2016 to 2018 (AUC = 0.847 in men, AUC = 0.901 in women). The performance of our hypertension model was considered significant based on the cumulative incidence calculated from a longitudinal dataset, the Korean Genome and Epidemiology Study dataset. We developed this hypertension prediction model using features that could be collected in a clinical office without difficulty. Individualized results may alert a person at high risk to modify unhealthy lifestyles.
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