Key result
A sex-specific clinical and lifestyle model predicts hypertension with an AUC up to ~0.85.
Why the study?
Hypertension is an increasing risk factor for cardiovascular disease and mortality, but few existing prediction models reflect its wide range of risk factors.
Can a sex-specific prediction model using easily accessible clinical and lifestyle variables accurately predict hypertension in Korean adults aged 40 years or older?
Observational
Can a sex-specific prediction model using easily accessible clinical and lifestyle variables accurately predict hypertension in Korean adults aged 40 years or older?
A newly developed sex-specific prediction model using easily accessible clinical variables showed good performance in predicting hypertension in Korean adults.
May inform sex-specific hypertension risk assessment in Koreans; leaves open external validation and clinical utility.
BACKGROUND 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. OBJECTIVE We constructed a sex-specific prediction model using Korean datasets, which included socioeconomic status, medical history, lifestyle-related variables, anthropometric status, and laboratory indices. METHODS 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. RESULTS 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 = 0.807 in men, AUC = 0.854 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. CONCLUSIONS 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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Seo et al. (2021) conducted an observational in Hypertension. Hypertension prediction model was evaluated on Hypertension classification model performance (AUC). A sex-specific hypertension prediction model using clinical and lifestyle variables demonstrated good performance, achieving an AUC of 0.807 in men and 0.854 in women.
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