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Conditional risk factors for atherosclerosis
Iftikhar J Kullo1, Christie M Ballantyne
1Department of Internal Medicine and Division of Cardiovascular Diseases, Mayo Clinic College of Medicine, Rochester, Minn 55905, USA. kullo.iftikhar@mayo.edu
Insights
Conventional risk factors for coronary heart disease (CHD) have limited accuracy. This review examines conditional risk factors like homocysteine and C-reactive protein to improve CHD risk prediction in asymptomatic individuals.
Area of Science:
- Cardiovascular Medicine
- Biomarkers
- Atherosclerosis Research
Background:
- Conventional risk factors for coronary heart disease (CHD) have limited predictive accuracy for atherosclerosis events.
- Many individuals without CHD events possess conventional risk factors, necessitating improved prediction models.
- Circulating biomarkers are being investigated to enhance CHD risk stratification.
Purpose of the Study:
- To review conditional risk factors for CHD prediction in asymptomatic individuals.
- To update clinicians on the utility of specific biomarkers in assessing cardiovascular risk.
- To discuss the mechanisms, assays, evidence, and clinical implications of these risk factors.
Main Methods:
- Literature review of conditional risk factors for CHD.
- Analysis of biomarkers including homocysteine, fibrinogen, lipoprotein(a), LDL particle size, and C-reactive protein.
- Evaluation of current clinical availability and utility of these risk factors.
Main Results:
- Conditional risk factors may refine CHD risk prediction beyond conventional factors.
- Evidence for association with CHD and clinical implications are discussed for each biomarker.
- Focus on biomarkers currently available to clinicians for risk assessment.
Conclusions:
- Conditional risk factors show potential for improving CHD risk prediction in asymptomatic populations.
- Understanding these biomarkers aids in better cardiovascular risk management.
- Further evaluation is needed to fully integrate these factors into clinical practice.
Abstract:
Although most patients who experience a coronary heart disease (CHD) event have one or more of the conventional risk factors for atherosclerosis, so do many people who have not yet experienced such an event. Therefore, predictive models based on conventional risk factors have a lower than desired accuracy, providing a stimulus to search for new tools to refine CHD risk prediction. In particular, there is intense interest in evaluating circulating biomarkers related to the atherosclerotic process that might add to our ability to better predict CHD risk. One such group of biomarkers was termed conditional risk factors in an American Heart Association/American College of Cardiology statement in 1999. The conditional risk factors include homocysteine, fibrinogen, lipoprotein(a), low-density lipoprotein particle size, and C-reactive protein. This review updates the conditional risk factors. The main focus is on the potential utility of these risk factors, which are currently available to clinicians, in the prediction of CHD risk in asymptomatic persons. The putative mechanisms of risk, available assays, evidence for association with CHD, and the clinical implications thereof are discussed for each of the risk factors.
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