Model for assessing cardiovascular risk in a Korean population

Area of Science:

• Cardiology
• Public Health
• Epidemiology

Background:

• Existing cardiovascular disease (CVD) prediction models for Asian populations are limited.
• Accurate CVD risk assessment is crucial for preventative strategies.

Purpose of the Study:

• To develop and validate a novel CVD risk prediction model tailored for an asymptomatic Korean population.
• To identify key clinical and biomarker predictors of cardiovascular events.

Main Methods:

• A cohort of 57,393 asymptomatic Korean adults (30-80 years) without prior CVD was established.
• Risk factors including demographics, clinical measurements, and biomarkers were assessed.
• A prediction model was developed using a training cohort and validated in a separate cohort, assessing discrimination and calibration.

Main Results:

• The final model incorporated age, diabetes, hypertension, smoking, family history of coronary heart disease, white blood cell count, creatinine, glycohemoglobin, atrial fibrillation, blood pressure, and cholesterol.
• The model demonstrated good predictive performance in both training (C-index=0.757) and validation cohorts (C-index=0.760 at 3 years, 0.782 at 5 years).

Conclusions:

• A feasible cardiovascular risk prediction model using traditional clinical factors and biomarkers was developed for asymptomatic Korean individuals.
• The model shows promising performance for predicting cardiovascular events in this specific population.