Literature DB >> 24122913

Very large database of lipids: rationale and design.

Seth S Martin1, Michael J Blaha, Peter P Toth, Parag H Joshi, John W McEvoy, Haitham M Ahmed, Mohamed B Elshazly, Kristopher J Swiger, Erin D Michos, Peter O Kwiterovich, Krishnaji R Kulkarni, Joseph Chimera, Christopher P Cannon, Roger S Blumenthal, Steven R Jones.   

Abstract

Blood lipids have major cardiovascular and public health implications. Lipid-lowering drugs are prescribed based in part on categorization of patients into normal or abnormal lipid metabolism, yet relatively little emphasis has been placed on: (1) the accuracy of current lipid measures used in clinical practice, (2) the reliability of current categorizations of dyslipidemia states, and (3) the relationship of advanced lipid characterization to other cardiovascular disease biomarkers. To these ends, we developed the Very Large Database of Lipids (NCT01698489), an ongoing database protocol that harnesses deidentified data from the daily operations of a commercial lipid laboratory. The database includes individuals who were referred for clinical purposes for a Vertical Auto Profile (Atherotech Inc., Birmingham, AL), which directly measures cholesterol concentrations of low-density lipoprotein, very low-density lipoprotein, intermediate-density lipoprotein, high-density lipoprotein, their subclasses, and lipoprotein(a). Individual Very Large Database of Lipids studies, ranging from studies of measurement accuracy, to dyslipidemia categorization, to biomarker associations, to characterization of rare lipid disorders, are investigator-initiated and utilize peer-reviewed statistical analysis plans to address a priori hypotheses/aims. In the first database harvest (Very Large Database of Lipids 1.0) from 2009 to 2011, there were 1 340 614 adult and 10 294 pediatric patients; the adult sample had a median age of 59 years (interquartile range, 49-70 years) with even representation by sex. Lipid distributions closely matched those from the population-representative National Health and Nutrition Examination Survey. The second harvest of the database (Very Large Database of Lipids 2.0) is underway. Overall, the Very Large Database of Lipids database provides an opportunity for collaboration and new knowledge generation through careful examination of granular lipid data on a large scale.
© 2013 Wiley Periodicals, Inc.

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Year:  2013        PMID: 24122913      PMCID: PMC6649455          DOI: 10.1002/clc.22214

Source DB:  PubMed          Journal:  Clin Cardiol        ISSN: 0160-9289            Impact factor:   2.882


  15 in total

1.  Estimation of biomarker distributions using laboratory data collected during routine delivery of medical care.

Authors:  Maurice Alan Brookhart; Jonathan V Todd; Xiaojuan Li; B Diane Reams; Virginia Pate; Abhijit V Kshirsagar
Journal:  Ann Epidemiol       Date:  2014-08-06       Impact factor: 3.797

2.  Patient-Level Discordance in Population Percentiles of the Total Cholesterol to High-Density Lipoprotein Cholesterol Ratio in Comparison With Low-Density Lipoprotein Cholesterol and Non-High-Density Lipoprotein Cholesterol: The Very Large Database of Lipids Study (VLDL-2B).

Authors:  Mohamed B Elshazly; Renato Quispe; Erin D Michos; Allan D Sniderman; Peter P Toth; Maciej Banach; Krishnaji R Kulkarni; Josef Coresh; Roger S Blumenthal; Steven R Jones; Seth S Martin
Journal:  Circulation       Date:  2015-07-02       Impact factor: 29.690

3.  Deficient serum 25-hydroxyvitamin D is associated with an atherogenic lipid profile: The Very Large Database of Lipids (VLDL-3) study.

Authors:  Joshua R Lupton; Kamil F Faridi; Seth S Martin; Sristi Sharma; Krishnaji Kulkarni; Steven R Jones; Erin D Michos
Journal:  J Clin Lipidol       Date:  2015-09-25       Impact factor: 4.766

4.  Comparison of a novel method vs the Friedewald equation for estimating low-density lipoprotein cholesterol levels from the standard lipid profile.

Authors:  Seth S Martin; Michael J Blaha; Mohamed B Elshazly; Peter P Toth; Peter O Kwiterovich; Roger S Blumenthal; Steven R Jones
Journal:  JAMA       Date:  2013-11-20       Impact factor: 56.272

5.  Assessing the Accuracy of Estimated Lipoprotein(a) Cholesterol and Lipoprotein(a)-Free Low-Density Lipoprotein Cholesterol.

Authors:  Weili Zheng; Michael Chilazi; Jihwan Park; Vasanth Sathiyakumar; Leslie J Donato; Jeffrey W Meeusen; Mariana Lazo; Eliseo Guallar; Krishnaji R Kulkarni; Allan S Jaffe; Raul D Santos; Peter P Toth; Steven R Jones; Seth S Martin
Journal:  J Am Heart Assoc       Date:  2022-01-13       Impact factor: 6.106

6.  Novel unbiased equations to calculate triglyceride-rich lipoprotein cholesterol from routine non-fasting lipids.

Authors:  Michel P Hermans; Sylvie A Ahn; Michel F Rousseau
Journal:  Cardiovasc Diabetol       Date:  2014-03-10       Impact factor: 9.951

7.  Narrowing sex differences in lipoprotein cholesterol subclasses following mid-life: the very large database of lipids (VLDL-10B).

Authors:  Kristopher J Swiger; Seth S Martin; Michael J Blaha; Peter P Toth; Khurram Nasir; Erin D Michos; Gary Gerstenblith; Roger S Blumenthal; Steven R Jones
Journal:  J Am Heart Assoc       Date:  2014-04-22       Impact factor: 5.501

8.  Effect of alirocumab on specific lipoprotein non-high-density lipoprotein cholesterol and subfractions as measured by the vertical auto profile method: analysis of 3 randomized trials versus placebo.

Authors:  Peter P Toth; Sara C Hamon; Steven R Jones; Seth S Martin; Parag H Joshi; Krishnaji R Kulkarni; Poulabi Banerjee; Corinne Hanotin; Eli M Roth; James M McKenney
Journal:  Lipids Health Dis       Date:  2016-02-13       Impact factor: 3.876

9.  Accuracy of low-density lipoprotein cholesterol estimation at very low levels.

Authors:  Renato Quispe; Aditya Hendrani; Mohamed B Elshazly; Erin D Michos; John W McEvoy; Michael J Blaha; Maciej Banach; Krishnaji R Kulkarni; Peter P Toth; Josef Coresh; Roger S Blumenthal; Steven R Jones; Seth S Martin
Journal:  BMC Med       Date:  2017-04-20       Impact factor: 8.775

10.  Vitamin D deficiency and non-lipid biomarkers of cardiovascular risk.

Authors:  Kamil F Faridi; Joshua R Lupton; Seth S Martin; Maciej Banach; Renato Quispe; Krishnaji Kulkarni; Steven R Jones; Erin D Michos
Journal:  Arch Med Sci       Date:  2017-06-12       Impact factor: 3.318

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