Literature DB >> 24672715

Validation of the friedewald formula in patients with metabolic syndrome.

José Knopfholz1, Caio César Diniz Disserol1, Andressa Jardim Pierin1, Fernanda Letícia Schirr1, Larissa Streisky1, Lilian Lumi Takito1, Patrícia Massucheto Ledesma1, José Rocha Faria-Neto1, Marcia Olandoski1, Claudio Leinig Pereira da Cunha1, Antonio Milton Bandeira1.   

Abstract

Currently, the Friedewald formula (FF) is the main method for evaluating low-density lipoprotein cholesterol (LDL-c). Recently, many limitations have emerged regarding its use, including patients with triglyceride levels ≥400 mg/dL, diabetes mellitus, and kidney or hepatic chronic diseases. We analyzed the use of the FF in patients with metabolic syndrome. We selected patients with known metabolic syndrome that fulfilled the National Cholesterol Education Program Expert Panel on Detection, Evaluation and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) Final Report and excluded patients with triglyceride levels ≥400 mg/dL and chronic liver and/or kidney disease. Using direct assays, we measured total cholesterol, high-density lipoprotein cholesterol, triglycerides, and LDL-c. Then, LDL-c was estimated using the FF and compared with the LDL-c by direct assay. The sample size was 135 patients. Using the FF, the mean LDL-c value was 124.4 ± 42.1 mg/dL; it was 125.1 ± 38.5 mg/dL by direct assay. The correlation coefficient between these two methods was 0.89, with statistical significance (P  value < 0.001). There were no significant differences between the patients with triglyceride levels >150 mg/dL (P = 0.618). In conclusion, FF is a good method for estimating LDL-c in patients with metabolic syndrome.

Entities:  

Year:  2014        PMID: 24672715      PMCID: PMC3941209          DOI: 10.1155/2014/261878

Source DB:  PubMed          Journal:  Cholesterol        ISSN: 2090-1283


1. Introduction

Metabolic syndrome (MS) comprises a group of metabolic abnormalities that are related to high cardiovascular risk, particularly for the development of coronary artery disease (CAD) [1]. MS is highly prevalent in Brazil, affecting approximately 30% of the population. The prevalence increases in older populations [2]. The main concern about MS is the development of CAD, which is a highly prevalent condition and a major cause of mortality. In the development of CAD, lipid metabolism, which is the formation of atherosclerotic plaque, plays a major role. Hypercholesterolemia is a lipid abnormality commonly related to atherosclerosis. Nevertheless, LDL-c, which is the major lipoprotein associated with CAD, is not a part of the diagnostic criteria of MS [3-5]. The physiological levels of LDL-c that are sufficient for lipid metabolism range from 25 to 60 mg/dL, and LDL-c is more atherogenic when it exceeds 100 mg/dL. Therefore, as previously described in the literature, lower levels of LDL-c reduce cardiovascular morbidity and mortality [6-8]. Cardiovascular risk stratification defines the LDL-c value target. Therefore, the LDL-c measurement technique requires standardization and good accuracy [6-10]. The Friedewald formula (FF) is an estimation of LDL-c level that uses the following levels of total cholesterol (TC), triglycerides (TG), and high-density lipoprotein cholesterol (HDL-c): LDL-c (mg/dL) = TC (mg/dL) − HDL-c (mg/dL) − TG (mg/dL)/5 [6, 11–13]. To be applied in the FF, the measurements of TC, HDL-c, and TG must be in mg/dL; the estimation differs and was not performed for the mmol/L measurements. The FF became the standard method for LDL-c assessment because it is economical and simpler than direct assays, the most accurate LDL-c measurement methods [9, 11–13]. FF has limitations under certain conditions, primarily when metabolic abnormalities alter the relationship between very-low-density lipoprotein cholesterol (VLDL-c) and TG, as in high hypertriglyceridemia (TG > 400 mg/dL) [11, 13–16]. Furthermore, new studies show considerable differences between the estimation and direct assessment of LDL-c in many other conditions [6, 7, 12, 13]. As in MS, there are changes in the disposition and metabolism of lipids; thus, the FF estimates LDL-c by assessing other lipid particles. Likely, its use in MS may not be reliable.

2. Materials and Methods

We selected patients with known metabolic syndrome that fulfilled the criteria outlined in the National Cholesterol Education Program Expert Panel on Detection, Evaluation and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) Final Report [6, 12]; three or more of the following components were present: increased waist circumference (≥102 cm for men and ≥88 cm  for women); triglycerides ≥ 150 mg/dL or drug treatment for elevated TG; low HDL-c (<40 mg/dL for men and <50 mg/dL for women) or drug treatment for low HDL-c; systolic blood pressure ≥ 130 mmHg, diastolic blood pressure ≥ 85 mmHg, or treatment with antihypertensive in patients with a history of hypertension; fasting glucose ≥ 100 mg/dL or treatment for high blood glucose. Patients who fulfilled the MS criteria, consented to provide a blood sample, and signed the informed consent form were included in the study. Patients who did not fulfill the MS criteria, did not sign the informed consent form, and had TG ≥ 400 mg/dL were excluded. All participants underwent a 12-hour fast. The following tests were performed (using a Selectra II analyzer with reagents and calibrators from ELITech): direct assays for TC, HDL-c, LDL-c, and TG. The results were applied in the FF, and then the LDL-c estimation could be performed. LDL-c was determined by a homogenous direct assay (i.e., colorimetry) using an ELITech kit. Colorimetry is a third generation method (a homogeneous assay with some reagents that can solubilize or specifically block these lipoproteins, dosing LDL-c alone in the same bucket with an enzymatic reaction) [17]. Thus, we could compare both LDL-c values (using the FF and by direct assay) and evaluate the reliability of the FF in the MS patients. The results were described as means, medians, minimum values, maximum values, and standard deviations (quantitative variables) or by frequency and percentiles (qualitative variables). For the assessment of the results of LDL-c using the FF and LDL-c by direct assay was used the Student's t-test for paired samples. To evaluate the correlation between both methods, Pearson's correlation coefficient was used. Scattergram data and a Bland-Altman diagram were used to evaluate the dispersion and differences between the results obtained using the FF and direct assay, and P values < 0.05 were considered to be statistically significant. Data were analyzed with the software Statistica v.8.0.

3. Results

The sample size comprised 135 individuals. Using the FF, the statistical analysis of LDL-c showed a mean value of 124.4 mg/dL (SD = 42.1 mg/dL); by direct assay, the mean value was 125.1 mg/dL (SD = 38.5 mg/dL). The difference between the FF and direct measurement showed strong correlation between both methods because the mean difference was −0.7 mg/dL, as shown in Figure 1.
Figure 1

Relationship between the LDL-c values using the FF and direct dosage.

We subdivided the patients based on their TG values to analyze whether the different methods used produced different values for this lipid. In the group of patients with TG ≤ 150 mg/dL (n = 50), no significant difference between the methods (P = 0.881) was observed; in the patient group with TG > 150 mg/dL, there was also no significant difference between the two methods (P = 0.618), as shown in Figure 2.
Figure 2

Evaluation of LDL-c values by triglyceride level with the FF and direct assay.

To assess the degree of association between the methods, we estimated the correlation coefficient between them, which equaled 0.89, with statistical significance (P < 0.001). Thus, based on the results of the statistical tests, we believe that there is no significant difference between the assessment of LDL-c using the FF and by direct measurement, as shown in Figure 3.
Figure 3

Scattergram data between LDL-c values by Friedewald formula and by direct assay.

As shown in Figure 4, it is possible to conclude that, in general, the FF underestimates the value of LDL-c compared to direct measurement. Moreover, the average difference between these methods appears to be more pronounced when the LDL-c is lower (by direct measurement): when LDL-c ≤ 121 mg/dL, the mean difference was 0.26 mg/dL, and for LDL-c > 121 mg/dL, the mean difference was −1.62 mg/dL. However, despite being approximately six times greater when the absolute difference in LDL-c > 121 mg/dL, this result is still too small and is clinically insignificant.
Figure 4

A Bland-Altman diagram correlating the absolute difference between the two methods and their means.

A minority of patients (n = 9) demonstrated an absolute difference >30 mg/dL between both methods, which could be clinically significant, as shown in Figure 4. Eight of these patients had TG > 150 mg/dL, but just one patient had a level >300 mg/dL. Considering that the mean value of TG in all patients with TG > 150 mg/dL in this study was 219.1 mg/dL, we concluded that patients with important differences in their LDL-c values (using the FF and direct assay) were not clustered in higher triglyceride level group. The relative difference between the calculated value of LDL-c using the FF and the direct measurement was that, on average, the value of the FF is 0.28% lower than the direct measurement.

4. Discussion

As the relationship between serum LDL-c and cardiovascular disease is well established, reliable methods of measuring this lipid are needed both to classify it and to treat our patients. However, recently, many studies have demonstrated limitations to the most widely used method for serum LDL-c estimation, the FF. Despite the classical indication for direct measurement of LDL-c as TG > 400 mg/dL, some studies have indicated that, for lower TG values, the FF is not as reliable. From 180 mg/dL, the FF already shows significant differences (overestimating LDL-c values) when compared to direct measurement methods [17, 18]. Similar results were shown by Charuruks and Milintagas [19], who indicated the direct measurement of LDL-c when TG ≥ 200 mg/dL because they found that the direct method was more precise and accurate than FF, even for TG levels between 200 and 399 mg/dL. One Brazilian study showed a similar conclusion for FF use [20]. Nevertheless, these findings do not align with those of our study, in which the LDL-c value was estimated with precision by the FF for any value of TG < 400 mg/dL. Some studies have shown that FF can also display discrepancies in low TG values [17, 21, 22]. When TG value was <70 mg/dL, the estimated LDL-c using the FF showed slightly lower values than that using the direct method [17]. Contradictory results have been demonstrated in other studies, in which serum LDL-c using the FF was higher than the homogeneous assay for TG < 100 or 200 mg/dL [21, 22]. In the present study, LDL-c values using the FF were virtually identical to the values by direct assay, particularly when TG ≤ 150 mg/dL (mean difference between LDL-c using the FF and direct measurement = 0.2). New studies are demonstrating the limited efficacy of FF in diabetic patients. Diabetes is the epitome of MS; thus, many of these studies have affirmed that this estimation is not as accurate for this syndrome as previously believed [6, 18, 23]. In diabetic patients, with or without insulin use, the FF underestimates, on average, 8% serum LDL-c, but it can underestimate more than 10% in patients with TG levels between 200 and 400 mg/dL [18]. We found only one study in the literature that correlated the efficacy of FF and a direct assay specifically in patients with MS. The authors found that the direct measurement method is more accurate than the FF in these patients; these results represent the limitations of this indirect method. However, the authors also noted that even direct assays have limitations in identifying small and dense LDL-c, which is abundant in these patients [23]. In the current study, all patients with MS and TG < 400 mg/dL demonstrated reliable LDL-c value estimates using the FF.

5. Conclusion

In conclusion, FF is a reliable method to estimate serum LDL-c in patients with MS.
  19 in total

1.  Executive Summary of The Third Report of The National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, And Treatment of High Blood Cholesterol In Adults (Adult Treatment Panel III).

Authors: 
Journal:  JAMA       Date:  2001-05-16       Impact factor: 56.272

Review 2.  [LDL: from metabolic syndrome to instability of the atherosclerotic plaque].

Authors:  Antonela F A Siqueira; Dulcinéia S P Abdalla; Sandra R G Ferreira
Journal:  Arq Bras Endocrinol Metabol       Date:  2006-05-23

3.  Variability in cholesterol measurements: comparison of calculated and direct LDL cholesterol determinations.

Authors:  G Schectman; M Patsches; E A Sasse
Journal:  Clin Chem       Date:  1996-05       Impact factor: 8.327

4.  A more valid measurement of low-density lipoprotein cholesterol in diabetic patients.

Authors:  S Hirany; D Li; I Jialal
Journal:  Am J Med       Date:  1997-01       Impact factor: 4.965

5.  [IV Brazilian Guideline for Dyslipidemia and Atherosclerosis prevention: Department of Atherosclerosis of Brazilian Society of Cardiology].

Authors:  Andrei C Sposito; Bruno Caramelli; Francisco A H Fonseca; Marcelo C Bertolami; Abrahão Afiune Neto; Aguinaldo David Souza; Ana Maria Pitta Lottenberg; Ana Paula Chacra; André A Faludi; Andréia A Loures-Vale; Antônio Carlos Carvalho; Bruce Duncan; Bruno Gelonese; Carisi Polanczyk; Carlos Roberto M Rodrigues Sobrinho; Carlos Scherr; Cynthia Karla; Dikran Armaganijan; Emílio Moriguchi; Francisco Saraiva; Geraldo Pichetti; Hermes Toros Xavier; Hilton Chaves; Jairo Lins Borges; Jayme Diament; Jorge Ilha Guimarães; José Carlos Nicolau; José Ernesto dos Santos; José Jayme Galvão de Lima; José Luiz Vieira; José Paulo Novazzi; José Rocha Faria Neto; Kerginaldo P Torres; Leonor de Almeida Pinto; Liliana Bricarello; Luiz Carlos Bodanese; Luiz Introcaso; Marcus Vinícius Bolívar Malachias; Maria Cristina Izar; Maria Eliane C Magalhães; Maria Inês Schmidt; Mariléia Scartezini; Moacir Nobre; Murilo Foppa; Neusa A Forti; Otávio Berwanger; Otávio C E Gebara; Otávio Rizzi Coelho; Raul C Maranhão; Raul Dias dos Santos Filho; Rosana Perim Costa; Sandhi Barreto; Sérgio Kaiser; Silvia Ihara; Tales de Carvalho; Tania Leme Rocha Martinez; Waldir Gabriel Miranda Relvas; Wilson Salgado
Journal:  Arq Bras Cardiol       Date:  2007-04       Impact factor: 2.000

6.  [Metabolic syndrome].

Authors:  Rafael Leite Luna
Journal:  Arq Bras Cardiol       Date:  2007-05       Impact factor: 2.000

Review 7.  Methods for measurement of LDL-cholesterol: a critical assessment of direct measurement by homogeneous assays versus calculation.

Authors:  Matthias Nauck; G Russell Warnick; Nader Rifai
Journal:  Clin Chem       Date:  2002-02       Impact factor: 8.327

8.  Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge.

Authors:  W T Friedewald; R I Levy; D S Fredrickson
Journal:  Clin Chem       Date:  1972-06       Impact factor: 8.327

9.  Validation of the Friedewald formula for the determination of low-density lipoprotein cholesterol compared with beta-quantification in a large population.

Authors:  André J Tremblay; Hugo Morrissette; Jean-Marc Gagné; Jean Bergeron; Claude Gagné; Patrick Couture
Journal:  Clin Biochem       Date:  2004-09       Impact factor: 3.281

10.  LDL cholesterol estimation in patients with the metabolic syndrome.

Authors:  Irene Gazi; Vasilis Tsimihodimos; Theodosios D Filippatos; Vasilios G Saougos; Eleni T Bairaktari; Alexandros D Tselepis; Moses Elisaf
Journal:  Lipids Health Dis       Date:  2006-04-06       Impact factor: 3.876

View more
  40 in total

1.  The association between carbohydrate quality index and anthropometry, blood glucose, lipid profile and blood pressure in people with type 1 diabetes mellitus: a cross-sectional study in Iran.

Authors:  Haniyeh Jebraeili; Sakineh Shabbidar; Zahra Sajjadpour; Saeideh Delshad Aghdam; Mostafa Qorbani; Asadollah Rajab; Gity Sotoudeh
Journal:  J Diabetes Metab Disord       Date:  2021-11-13

2.  Predicting type 2 diabetes mellitus among fishermen in Cape Coast: a comparison between the FINDRISC score and the metabolic syndrome.

Authors:  Richard K D Ephraim; Victor Boachie Owusu; Jephthah Asiamah; Arnold Mills; Albert Abaka-Yawson; Godsway Edem Kpene; Precious Kwablah Kwadzokpui; Samuel Adusei
Journal:  J Diabetes Metab Disord       Date:  2020-10-08

3.  Lipid status association with 25-hydroxy vitamin D: Cross sectional study of end stage renal disease patients.

Authors:  Neda Milinković; Marija Sarić; Snežana Jovičić; Duško Mirković; Višnja Ležaić; Svetlana Ignjatović
Journal:  J Med Biochem       Date:  2020-09-02       Impact factor: 3.402

4.  Is data mining approach a best fit formula for estimation of low-density lipoprotein cholesterol?

Authors:  Rajlaxmi Sarangi; Jyotirmayee Bahinipati; Mona Pathak; Srikrushna Mahapatra
Journal:  J Family Med Prim Care       Date:  2021-01-30

5.  Effect of 5 years of exercise training on the cardiovascular risk profile of older adults: the Generation 100 randomized trial.

Authors:  Jon Magne Letnes; Ida Berglund; Kristin E Johnson; Håvard Dalen; Bjarne M Nes; Stian Lydersen; Hallgeir Viken; Erlend Hassel; Sigurd Steinshamn; Elisabeth Kleivhaug Vesterbekkmo; Asbjørn Støylen; Line S Reitlo; Nina Zisko; Fredrik H Bækkerud; Atefe R Tari; Jan Erik Ingebrigtsen; Silvana B Sandbakk; Trude Carlsen; Sigmund A Anderssen; Maria A Fiatarone Singh; Jeff S Coombes; Jorunn L Helbostad; Øivind Rognmo; Ulrik Wisløff; Dorthe Stensvold
Journal:  Eur Heart J       Date:  2022-06-01       Impact factor: 35.855

6.  Rigiscan Evaluation of Men with Diabetes Mellitus and Erectile Dysfunction and Correlation with Diabetes Duration, Age, BMI, Lipids and HbA1c.

Authors:  Daniel Peter Andersson; Urban Ekström; Mikael Lehtihet
Journal:  PLoS One       Date:  2015-07-17       Impact factor: 3.240

7.  Beneficial effects of Hibiscus rosa-sinensis L. flower aqueous extract in pregnant rats with diabetes.

Authors:  Luana Alves Freitas Afiune; Thaís Leal-Silva; Yuri Karen Sinzato; Rafaianne Queiroz Moraes-Souza; Thaigra Sousa Soares; Kleber Eduardo Campos; Ricardo Toshio Fujiwara; Emilio Herrera; Débora Cristina Damasceno; Gustavo Tadeu Volpato
Journal:  PLoS One       Date:  2017-06-23       Impact factor: 3.240

8.  Safety evaluation of a vaccine: Effect in maternal reproductive outcome and fetal anomaly frequency in rats using a leishmanial vaccine as a model.

Authors:  Rafaianne Q Moraes-Souza; Ana Paula Reinaque; Thaigra S Soares; Ana Luiza T Silva; Rodolfo C Giunchetti; Maria A S Takano; Milena A Akamatsu; Flávia S Kubrusly; Fernanda Lúcio-Macarini; Isaias Raw; Dmitri Iourtov; Paulo Lee Ho; Lilian L Bueno; Ricardo T Fujiwara; Gustavo T Volpato
Journal:  PLoS One       Date:  2017-03-01       Impact factor: 3.240

9.  The Effects of Synbiotic Supplementation on Glycemic Status, Lipid Profile, and Biomarkers of Oxidative Stress in Type 1 Diabetic Patients. A Placebo-Controlled, Double-Blind, Randomized Clinical Trial.

Authors:  Ahmad Zare Javid; Majid Aminzadeh; Mohammad Hosein Haghighi-Zadeh; Mona Jamalvandi
Journal:  Diabetes Metab Syndr Obes       Date:  2020-03-02       Impact factor: 3.168

10.  Testosterone and gonadotropins but not SHBG vary with CKD stages in young and middle aged men.

Authors:  Britta Hylander; Mikael Lehtihet
Journal:  Basic Clin Androl       Date:  2015-12-02
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