A Cardiovascular Disease (CVD) Classification Model for Individuals With Obesity: Multi‐Ethnic Validation Based on Multiple Metabolic Indicators
Authors' conclusion
This study developed and validated a nomogram for the classification of prevalent CVD in individuals with obesity, providing a validated model optimized for the population with obesity.
Study context
- Population
- Individuals with obesity; sensitivity analysis with a unified BMI standard in the Korea cohort
- Comparison
- Internal validation vs External validation
- Outcome
- Classification of prevalent CVD (model performance: AUC, calibration, decision curve analysis (DCA))
Methodological detailsinternal and external validation, LASSO regression, multivariate logistic model, nomogram, Web-based dynamic nomogram implemented
- Internal and external validation
- LASSO regression
- Multivariate logistic model
- Nomogram
- Web-based dynamic nomogram implemented
Performance
As reported in the abstract
Model discrimination and calibration
| Test or model | AUC | Hosmer-Lemeshow p value |
|---|---|---|
| Internal validation | 0.799 | 0.823 |
| External validation | 0.821 | 0.083 |
AUC
Internal validation0.799
External validation0.821
Hosmer-Lemeshow p value
Internal validation0.823
External validation0.083
Original publication
A CVD Classification Model for Individuals With Obesity: Multi‐Ethnic Validation Based on Multiple Metabolic Indicators. Obesity (Silver Spring). Published 21 July 2026. doi:10.
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