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Cited by 21Blood Pressure and Hypertension StudiesArtificial Intelligence in HealthcareHealth Promotion and Cardiovascular Prevention

Integrating health data-driven machine learning algorithms to evaluate risk factors of early stage hypertension at different levels of HDL and LDL cholesterol

Open access
Liao, Pen-Chih, Chen, Ming-Shu, Jhou, Mao-Jhen, Chen, Tsan-Chi, Yang, Chih-Te, Lu, Chi-Jie·2022·Diagnostics
DOI 10.3390/diagnostics12081965PMC PMC9407063
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Abstract

PURPOSE: Cardiovascular disease (CVD) is a major worldwide health burden. As the risk factors of CVD, hypertension, and hyperlipidemia are most mentioned. Early stage hypertension in the population with dyslipidemia is an important public health hazard. This study was the application of data-driven machine learning (ML), demonstrating complex relationships between risk factors and outcomes and promising predictive performance with vast amounts of medical data, aimed to investigate the association between dyslipidemia and the incidence of early stage hypertension in a large cohort with normal blood pressure at baseline. METHODS: This study analyzed annual health screening data for 71,108 people from 2005 to 2017, including data for 27 risk-related indicators, sourced from the MJ Group, a major health screening center in Taiwan. We used five machine learning (ML) methods-stochastic gradient boosting (SGB), multivariate adaptive regression splines (MARS), least absolute shrinkage and selection operator regression (Lasso), ridge regression (Ridge), and gradient boosting with categorical features support (CatBoost)-to develop a multi-stage ML algorithm-based prediction scheme and then evaluate important risk factors at the early stage of hypertension, especially for groups with high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) levels within or out of the reference range. RESULTS: Age, body mass index, waist circumference, waist-to-hip ratio, fasting plasma glucose, and C-reactive protein (CRP) were associated with hypertension. The hemoglobin level was also a positive contributor to blood pressure elevation and it appeared among the top three important risk factors in all LDL-C/HDL-C groups; therefore, these variables may be important in affecting blood pressure in the early stage of hypertension. A residual contribution to blood pressure elevation was found in groups with increased LDL-C. This suggests that LDL-C levels are associated with CPR levels, and that the LDL-C level may be an important factor for predicting the development of hypertension. CONCLUSION: The five prediction models provided similar classifications of risk factors. The results of this study show that an increase in LDL-C is more important than the start of a drop in HDL-C in health screening of sub-healthy adults. The findings of this study should be of value to health awareness raising about hypertension and further discussion and follow-up research.

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  • Atherosclerotic cardiovascular disease is associated with high serum LDL-C and HDL-C levels.

    “Atherosclerotic cardiovascular disease is associated with high serum LDL-C and HDL-C levels (Liao et al., 2022).”

    From Lactiplantibacillus plantarum N4 ameliorates lipid metabolism and gut microbiota structure in high fat diet-fed rats (2024) · cites this paper as Liao et al., 2022

    The Introduction identifies high LDL-C and low—not high—HDL-C as risk factors for cardiovascular disease. The Discussion likewise says increased LDL-C or decreased HDL-C plays a role in CVD. Thus the LDL-C portion aligns with the paper, but the claim reverses its HDL-C finding. (LLM, conf=0.88)

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Authors
Liao, P.-C., Chen, M.-S., Jhou, M.-J., Chen, T.-C., Yang, C.-T., & Lu, C.-J.
Affiliations
  • Far Eastern Memorial Hospital (TW)
  • Asia Eastern University of Science and Technology (TW)
  • Fu Jen Catholic University (TW)
  • Tamkang University (TW)
Corresponding author
Lu, Chi-Jie
ORCID
Venue
Diagnostics
Publisher
MDPI AG
Published
2022-08-14
Volume
12
Issue
8
Pages
1965
ISSN
2075-4418 (ISSN-L)
DOI
10.3390/diagnostics12081965
PMC
PMC9407063
OpenAlex
W4291366997
Cited by
21
References
85
Citations by year
2026: 2 · 2025: 5 · 2024: 8 · 2023: 5 · 2022: 1
FWCI
3.31
Type
journal article
Language
en
Open access
Licence
Locations
  • Diagnostics (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Tamkang University Institutional Repository (TKUIR) (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • Far Eastern Memorial Hospital (NSC-RD-110-1-10-503, NSC-RD-110-1-10-510, MOST-110-2221-E-030-010, MOST-110-2622-H-161-001)
  • Ministry of Science and Technology (NSC-RD-110-1-10-503, NSC-RD-110-1-10-510, MOST-110-2221-E-030-010, MOST-110-2622-H-161-001)
Topics
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Blood Pressure and Hypertension Studies
  • Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Health Promotion and Cardiovascular Prevention
Keywords
early-stage hypertension, dyslipidemia, HDL cholesterol, LDL cholesterol, cardiovascular risk factors, hypertension risk prediction, C-reactive protein, hemoglobin, hyperlipidemia, health screening, machine learning prediction models

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