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[Clinical evaluation of risk factors for coronary heart disease]

Ya-ping Jin1, Guang-ming Qin, Song-zhao Zhang

  • 1The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310009, China.

Insights

This study found that hyperlipidemia history predicts coronary heart disease (CHD). High-density lipoprotein cholesterol ratio and lipoprotein(a) levels are strong predictors for high blood lipids, while high-sensitivity C-reactive protein indicates coronary inflammation.

Area of Science:

  • Cardiology
  • Biochemistry
  • Public Health

Context:

  • Coronary heart disease (CHD) remains a leading cause of mortality worldwide.
  • Identifying reliable risk factors and predictors is crucial for early detection and prevention of CHD.
  • Coronary angiography is a standard diagnostic tool for assessing coronary artery lesions.

Purpose:

  • To investigate the association between established coronary heart disease (CHD) risk factors and the presence and severity of coronary artery lesions.
  • To evaluate the predictive value of various biomarkers and clinical factors in identifying individuals with coronary artery disease.

Summary:

  • A study of 341 patients undergoing coronary angiography revealed significant differences in age, diabetes, family history, smoking, HDL-C, LDL-C, TC/HDL-C, Lp(a), fibrinogen, and hs-CRP between patients with and without coronary lesions.
  • Severity of coronary artery lesions correlated significantly with hs-CRP, Lp(a), TC/HDL-C, fibrinogen, hyperlipidemia, TC, LDL-C, and TG.
  • ROC curve analysis indicated strong predictive values for hs-CRP, TC/HDL-C, and Lp(a) in identifying coronary artery disease.

Impact:

  • Past hyperlipidemia history emerged as a significant predictor for CHD occurrence.
  • The ratio of total cholesterol to HDL-C (TC/HDL-C) and lipoprotein(a) [Lp(a)] levels show strong potential as screening tools for dyslipidemia.
  • High-sensitivity C-reactive protein (hs-CRP) demonstrates excellent predictive value for active coronary inflammatory processes, aiding in risk stratification.
Abstract

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