Development of a Predictive Model for Metabolic Syndrome Using Noninvasive Data and its Cardiovascular Disease Risk Assessments: Multicohort Validation Study

This study developed a noninvasive predictive model for metabolic syndrome with strong performance across diverse validation cohorts. By enabling early risk identification without laboratory tests, the model enhances accessibility in primary care and large-scale screenings. Its ability to predict long-term CVD risk supports proactive intervention strategies, potentially reducing the burden of cardiometabolic diseases. Further research should refine the model with additional clinical factors and broader population validation to maximize its clinical impact.

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Publication Details

Journal
Journal of Medical Internet Research
Published
2025-05-02
DOI
https://doi.org/10.2196/67525
Citations
5
Primary Topic
Nutritional Studies and Diet
Type
article
Field-Weighted Citation Impact
9.39
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article

Development of a Predictive Model for Metabolic Syndrome Using Noninvasive Data and its Cardiovascular Disease Risk Assessments: Multicohort Validation Study

Seogsong Jeong, Jin-Hyun Park, HwaMin Lee�, Gang-Jee Ko et al.
5 citations
Journal of Medical Internet Research
Nutritional Studies and Diet
9.39
article

Development of a Predictive Model for Metabolic Syndrome Using Noninvasive Data and its Cardiovascular Disease Risk Assessments: Multicohort Validation Study

Seogsong Jeong, Jin-Hyun Park, HwaMin Lee�, Gang-Jee Ko, Inyong Jeong
article en
5 citations

Abstract

This study developed a noninvasive predictive model for metabolic syndrome with strong performance across diverse validation cohorts. By enabling early risk identification without laboratory tests, the model enhances accessibility in primary care and large-scale screenings. Its ability to predict long-term CVD risk supports proactive intervention strategies, potentially reducing the burden of cardiometabolic diseases. Further research should refine the model with additional clinical factors and broader population validation to maximize its clinical impact.

Journal of Medical Internet ResearchVol. 27
Korea University (KR), Korea University Medical Center (KR)
Good health and well-being
Openalex Percentile: Top 2%
Nutritional Studies and Diet
9.39
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