Why the study?
Does a diagnostic algorithm using apoB, TG, and total cholesterol identify individuals with worse cardiovascular risk profiles and subclinical atherosclerosis in the general population?
Does a diagnostic algorithm using apoB, TG, and total cholesterol identify individuals with worse cardiovascular risk profiles and subclinical atherosclerosis in the general population?
A diagnostic algorithm using apoB, TG, and total cholesterol identifies a high prevalence of dyslipoproteinemias associated with increased subclinical atherosclerosis in the general population.
May support apoB-TG-total cholesterol algorithm to identify higher subclinical atherosclerosis risk; hypothesis-generating and requires prospective validation.
BACKGROUND: We applied a diagnostic algorithm using apolipoprotein B (apoB) in combination with triglycerides (TG) and total cholesterol to determine the prevalence of dyslipoproteinemias in the general population. We also characterized the overall cardiovascular (CV) risk profiles, including arterial structure and function as measured with a panel of noninvasive parameters. DESIGN: Clinical and biochemical characteristics and noninvasive measurements of atherosclerosis (NIMA) were determined in 1517 individuals, aged 50-70 years. RESULTS: In general, all dyslipoproteinemias were characterized by a worse CV risk profile and deteriorated outcomes of NIMA compared to those with normal apolipoprotein B (< 1·2 g L(-1)) and TG (< 1·5 mM) levels. The prevalence of hyperapoB-hyperTG was 15·1%, and these individuals showed the most abnormal atheroma-related parameters: reduced ankle-brachial-index at rest (-3·5%) and after exercise (-9·8%), increased intima-media thickness (+5·5%) and more carotid plaques (+39·1%). The prevalence of normoapoB-hyperTG because of increased VLDL was 18·1% and 2·3% because of increased chylomicrons and VLDL, and in these groups, the parameters related to stiffness (e.g. pulse-wave-velocity +7·6% and +5·2%, respectively) were most abnormal. Adjustment for apolipoprotein B (apoB) reduced differences in NIMA in the hyperapoB-hyperTG group, whereas adjustment for TG reduced differences in NIMA in the normoapoB-hyperTG group. CONCLUSIONS: The overall prevalence of dyslipoproteinemias according to the algorithm was approximately 40% in the Dutch population. The different dyslipoproteinemias showed a less favourable CV risk profile and deteriorated NIMA parameters, reflecting increased subclinical atherosclerosis. Furthermore, different effects on different NIMA parameters were observed in the different dyslipoproteinemias.
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Holewijn et al. (2010) studied this question.
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