Association Between Ratio of Cholesterols and Coronary Artery Stenosis According to Low-Density

So Ree Kim1, Mi-Na Kim1, Hee-Dong Kim2

  • 1Division of Cardiology, Korea University Anam Hospital, Seoul, Korea.

Insights

Cholesterol ratios, not just LDL-C, are linked to coronary artery disease (CAD) risk in Korean adults. These associations persist even with statin use or when LDL-C is within target ranges, highlighting their importance in CAD assessment.

Area of Science:

  • Cardiology
  • Lipid Metabolism
  • Preventive Medicine

Background:

  • Low-density lipoprotein cholesterol (LDL-C) is a primary target for preventing atherosclerotic cardiovascular disease.
  • Coronary artery disease (CAD) can still develop in individuals with recommended LDL-C levels.
  • Understanding alternative lipid markers is crucial for comprehensive CAD risk assessment.

Purpose of the Study:

  • To investigate the association between various lipid parameters and CAD in Korean patients with suspected angina.
  • To evaluate if these associations are influenced by statin use or achieved LDL-C target levels.

Main Methods:

  • Analysis of data from 2,410 Korean adults undergoing coronary angiography (2012-2022).
  • CAD defined as ≥50% stenosis in major coronary arteries.
  • Principal component analysis and multivariable logistic regression used to assess lipid parameter associations, with NRI and IDI for model discrimination.

Main Results:

  • Cholesterol ratios (Total Cholesterol/HDL-C, non-HDL-C/HDL-C, LDL-C/HDL-C) were significantly associated with CAD.
  • These associations were consistent across different statin use statuses and LDL-C levels.
  • Cholesterol ratios improved the predictive performance of models for CAD detection.

Conclusions:

  • Cholesterol ratios demonstrate significant cross-sectional associations with CAD in a Korean population.
  • The predictive value of these ratios for CAD is independent of statin therapy and LDL-C control.
  • Cholesterol ratios may offer valuable insights beyond LDL-C for assessing CAD risk.
Abstract

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