Coronary Artery Disease Prediction in Korean Patients with Familial Hypercholesterolemia: Analysis Involving Cholesterol Efflux Capacity.
Patients with familial hypercholesterolemia (FH) are at high risk of coronary artery disease (CAD), and its prediction is of great clinical importance. This study aimed to identify predictors of CAD and construct an effective risk prediction model for Korean patients with FH.
Clinical and laboratory data of 245 patients were collected from the Korean FH registry. CAD was defined as ≥50% coronary stenosis on invasive or computed tomographic angiography. The cholesterol efflux capacity (CEC) was measured using J774A1 cells and radiolabeled cholesterol. Predictors of CAD were identified by multivariable logistic regression analysis, and the best-performing prediction model was determined based on its statistical indices.
The participants' mean age was 49.1 years; 92 (37.6%) were male, and 41 (16.7%) had CAD. Age [odds ratio (OR) 1.05; p=0.02], hypertension (OR 7.28; p<0.0001), low-density lipoprotein-cholesterol (OR 1.60; p=0.02), and high-density lipoprotein-cholesterol (HDL-C) (OR 0.93; p=0.002) were identified as predictors of CAD in the multivariable analysis. In another analysis, age, hypertension, body mass index (OR 1.16; p=0.03), and apolipoprotein A1 (OR 0.97; p=0.002) were predictive of CAD. CEC did not have a significant predictive value. The best-performing CAD prediction model included six clinical and laboratory variables, with an area under the curve of 0.878. The effects of hypertension, smoking, and HDL-C were particularly influential.
Traditional risk factors, including hypertension and HDL-C, were predictors of CAD in Korean patients with FH, whereas CEC was not. The resulting CAD prediction model demonstrated satisfactory performance in this population.
Clinical and laboratory data of 245 patients were collected from the Korean FH registry. CAD was defined as ≥50% coronary stenosis on invasive or computed tomographic angiography. The cholesterol efflux capacity (CEC) was measured using J774A1 cells and radiolabeled cholesterol. Predictors of CAD were identified by multivariable logistic regression analysis, and the best-performing prediction model was determined based on its statistical indices.
The participants' mean age was 49.1 years; 92 (37.6%) were male, and 41 (16.7%) had CAD. Age [odds ratio (OR) 1.05; p=0.02], hypertension (OR 7.28; p<0.0001), low-density lipoprotein-cholesterol (OR 1.60; p=0.02), and high-density lipoprotein-cholesterol (HDL-C) (OR 0.93; p=0.002) were identified as predictors of CAD in the multivariable analysis. In another analysis, age, hypertension, body mass index (OR 1.16; p=0.03), and apolipoprotein A1 (OR 0.97; p=0.002) were predictive of CAD. CEC did not have a significant predictive value. The best-performing CAD prediction model included six clinical and laboratory variables, with an area under the curve of 0.878. The effects of hypertension, smoking, and HDL-C were particularly influential.
Traditional risk factors, including hypertension and HDL-C, were predictors of CAD in Korean patients with FH, whereas CEC was not. The resulting CAD prediction model demonstrated satisfactory performance in this population.
Authors
Lee Lee, Sheen Sheen, Seok Seok, Lee Lee, Kyun Kyun, Ann Ann, Lee Lee, Lee Lee
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