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Method for estimating high sdLDL-C by measuring triglyceride and apolipoprotein B levels

Overview of attention for article published in Lipids in Health and Disease, January 2017
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Title
Method for estimating high sdLDL-C by measuring triglyceride and apolipoprotein B levels
Published in
Lipids in Health and Disease, January 2017
DOI 10.1186/s12944-017-0417-6
Pubmed ID
Authors

Toshiyuki Hayashi, Shinji Koba, Yasuki Ito, Tsutomu Hirano

Abstract

We previously developed an assay to directly measure small dense (sd) low-density lipoprotein cholesterol (LDL-C) levels, which is not widely used in general clinical practice. Therefore, we propose a simpler method, "LDL window," that uses conventional methods for estimating high sdLDL-C levels. We analyzed our previous studies (2006-2008) on healthy subjects and patients with type 2 diabetes and coronary artery disease (CAD). The sdLDL-C level was measured using the precipitation method, and LDL size was determined using gradient gel electrophoresis. The "LDL window" comprises the estimation of LDL particle number and size. We adopted apolipoprotein B (apoB) for the estimation of the LDL particle number and used 110 mg/dL as the cutoff value for hyper-apoB. Triglycerides (TGs) are a powerful inverse determinant of LDL particle size. Therefore, we adopted TG for the estimation of the LDL particle size and used 150 mg/dL as the cutoff value for hyper-TG. Subjects were stratified into the following four subgroups: normal, hyper-TG, hyper-apoB, and hyper-TG/-apoB. Non-high-density lipoprotein cholesterol (non-HDL-C) is a surrogate marker for apoB; therefore, the "alternative LDL window" comprised non-HDL-C (cutoff, 170 mg/dL) and TG. The top quartile (Q4) of sdLDL-C (>31 mg/dL) doubled in patients with diabetes and CAD. The hyper-TG/-apoB group in the "LDL window" represented >90% Q4 and <4% Q1 and Q2, irrespective of the subjects. The sdLDL-C levels in the hyper-TG/-apoB group were 50% higher in patients with diabetes and CAD than those in controls. Similar results were obtained using the "alternative LDL window." Our proposed "LDL window" may help identify patients at high risk of CAD independent of LDL-C.

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Mendeley readers

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The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 40 100%

Demographic breakdown

Readers by professional status Count As %
Other 8 20%
Student > Master 5 13%
Researcher 4 10%
Student > Postgraduate 3 8%
Professor 2 5%
Other 6 15%
Unknown 12 30%
Readers by discipline Count As %
Medicine and Dentistry 13 33%
Biochemistry, Genetics and Molecular Biology 8 20%
Agricultural and Biological Sciences 2 5%
Nursing and Health Professions 1 3%
Sports and Recreations 1 3%
Other 1 3%
Unknown 14 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 August 2017.
All research outputs
#20,230,146
of 24,871,898 outputs
Outputs from Lipids in Health and Disease
#1,078
of 1,572 outputs
Outputs of similar age
#322,497
of 429,192 outputs
Outputs of similar age from Lipids in Health and Disease
#20
of 28 outputs
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