Low-density lipoprotein cholesterol estimation by a new formula in Indian population

Anandaraja, S; Narang, Rajiv; Godeswar, R.; Laksmy, R.; Kk, Talwar

doi:10.1016/j.ijcard.2004.05.009

Cited by 118 publications

(125 citation statements)

References 11 publications

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“…Although a good correlation exists between calculated LDL-C and M-LDL-C, the underestimation of LDL-C according to this formula has been shown in previous studies in the general population, as well as in those with diabetes mellitus. 20,21 Attempts to derive and validate further equations for LDL-C calculation have not been widely adopted, 22,23 and the Friedewald formula remains the recommended method in clinical practice and most National Lipid Guidelines. 4,5,24 Martin et al 25 after evaluating over 1.3 million lipid samples quantified by ultracentrifugation recently recommended an adjustable factor for the TG-to-VLDL ratio, instead of using a fixed factor of 5 (when using mg/dL), based on TG and non-HDL-cholesterol levels.…”

Section: Discussionmentioning

confidence: 99%

Low-density lipoprotein cholesterol levels in adults with type 2 diabetes: An alternative equation for accurate estimation and improved cardiovascular risk classification

Kheng

Fang

et al. 2014

Diabetes and Vascular Disease Research

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Low-density lipoprotein cholesterol (LDL-C) is a major risk factor for atherosclerotic disease. Despite its limitations, Friedewald-calculated LDL-C (F-LDL-C) remains widely used for LDL-C determination. In this observational study of 1999 adults with type 2 diabetes mellitus (T2DM), we compare the accuracy of F-LDL-C to directly measured LDL-C (M-LDL-C) and derived and validated a new [SMART2D (Singapore Study of MAcro-angiopathy and Micro-Vascular Reactivity in Type 2 Diabetes)] formula to estimate LDL-C. From 1000 randomly selected patients, M-LDL-C was compared to F-LDL-C. Using multiple linear regression to identify independent predictors for M-LDL-C, the SMART2D equation was derived and subsequently validated in the next 981 patients. F-LDL-C was 0.367 (0.216) mmol/L lower than M-LDL-C. This difference was −0.009 (0.189) for SMART2D-LDL-C. Using F-LDL-C, 27% with M-LDL-C ≥2.6 mmol/L were classified as LDL-C <2.6 mmol/L, reduced to 2.1% when using SMART2D-LDL-C. With F-LDL-C, misclassification was greater when triglycerides were ≥2.2 mmol/L, especially for the lower LDL-C cut-offs (1.8 and 2.6 mmol/L), and this was markedly improved with SMART2D-LDL-C. In conclusion, in T2DM, F-LDL-C underestimates M-LDL-C, with misclassifications that may potentially have an impact on therapeutic decisions in T2DM. The SMART2D equation improves accuracy of estimate, reducing misclassifications. Trials will be needed to ascertain the clinical significance of these findings.

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Section: Discussionmentioning

confidence: 99%

Low-density lipoprotein cholesterol levels in adults with type 2 diabetes: An alternative equation for accurate estimation and improved cardiovascular risk classification

Kheng

Fang

et al. 2014

Diabetes and Vascular Disease Research

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“…To recreate a 1000mg/day cholesterol intake, the events were altered to reflect an intake of 291.667 FC and 41.667mg CE 3 times a day. Lin and Connor (1980) did not report LDL-C or HDL-C values, therefore LDL-C was calculated from total cholesterol and triglyceride values using the equation below, in which LDL-C can be calculated in the absence of HDL-C data (Anandaraja et al, 2005). When the daily rate of cholesterol ingestion was raised, LDL-C increased from an initial value of 66.32mg/dL, to a steady state value of ~115mg/dL after one week.…”

Section: Comparison With Clinical Datamentioning

confidence: 99%

Mathematically modelling the dynamics of cholesterol metabolism and ageing

et al. 2016

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“…renal failure or diabetes) [2,11], but is widely used. Several other formulae have been developed, but these did not perform better than Friedewald's calculation [12][13][14] or had varying results in different population groups [10,[15][16][17][18][19] and including those considering TG ratios [20,21]. In the latest study validating a novel formula in comparison with Friedewald's calculation and the LDL-C reference method in 23 055 patients, the benefits over…”

Section: Introductionmentioning

confidence: 99%

Comparison of equations for the calculation of LDL-cholesterol in hospitalized patients

Martins

Olorunju

Murray

et al. 2015

Clinica Chimica Acta

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Highlights• We evaluated the Friedewald Equation and three other recently developed formulae.• The de Cordova, Chen & Hattori formulae were used in patients with co-morbidities.• More than 14 000 lipid profiles were compared with direct measurement of LDL-C.• The Hattori formula showed the best performance over all lipid values.• Alternative formulae should be implemented in hospitalized patients. Conclusions: We observe favorable correlations of the de Cordova formula withFriedewald at low TG values. However, the Hattori formula appears to be best for application in hospitalized patients, even at extreme lipid values.

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Low-density lipoprotein cholesterol estimation by a new formula in Indian population

Cited by 118 publications

References 11 publications

Low-density lipoprotein cholesterol levels in adults with type 2 diabetes: An alternative equation for accurate estimation and improved cardiovascular risk classification

Low-density lipoprotein cholesterol levels in adults with type 2 diabetes: An alternative equation for accurate estimation and improved cardiovascular risk classification

Mathematically modelling the dynamics of cholesterol metabolism and ageing

Comparison of equations for the calculation of LDL-cholesterol in hospitalized patients

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