Literature DB >> 24448679

Comparison of LDL-cholesterol estimate using the Friedewald formula and the newly proposed de Cordova formula with a directly measured LDL-cholesterol in a healthy South African population.

Chinelo P Onyenekwu1, Mariza Hoffmann2, Francois Smit3, Tandi E Matsha4, Rajiv T Erasmus5.   

Abstract

BACKGROUND: The accurate determination of low density lipoprotein cholesterol (LDL-c) is pertinent in clinical practice. Most laboratories employ the Friedewald formula, for convenient estimation of LDL-c, despite its shortfalls. Different formulae have been proposed for use, for more accurate but convenient estimation of LDL-c. Here, we compare a new formula recently proposed by de Cordova et al., with that of Friedewald and LDL-c determined by a homogeneous assay. We also assess its performance at very low TG levels against the modified Friedewald formula recommended by Ahmadi et al.
METHODS: A database of 587 adults from the 'Establishing Reference Intervals for Selected Analytes in South Africa' study was utilized. Fasting samples were assayed for lipids. LDL-c was determined by the Daiichi method. Performance of the Friedewald and the de Cordova formulae was compared. This was exclusively repeated at very low TG levels (<1.13 mmol/L), this time, including the Ahmadi formula.
RESULTS: The Friedewald formula and the de Cordova formula both had high correlations with the direct LDL-c (r = 0.98 and r = 0.97, respectively), although the latter showed an inconsistent bias at different LDL-c levels. The two formulae had a higher correlation (r = 0.98) than the Ahmadi formula (r = 0.92) at very low TG levels.
CONCLUSIONS: The Friedewald formula showed better agreement with the direct LDL-c than the de Cordova formula, at various LDL-c levels, in our population. It also performed better than the Ahmadi formula at very low TG levels. We therefore advise that it remains the formula of choice for LDL-c estimation in South Africa.
© The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Entities:  

Keywords:  Lipids; analytes; evaluation of new methods; laboratory methods; statistics

Mesh:

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Year:  2014        PMID: 24448679     DOI: 10.1177/0004563214520750

Source DB:  PubMed          Journal:  Ann Clin Biochem        ISSN: 0004-5632            Impact factor:   2.057


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