A method for estimating low-density lipoprotein (LDL-c) cholesterol

Abstract

The invention relates to a method that can be applied instead of clinical diagnosis of cardiovascular diseases or LDL-C measurement.

Description

[0001] A METHOD FOR ESTIMATING LOW-DENSITY LIPOPROTEIN (LDL-C) CHOLESTEROL

[0002] Technical Field

[0003] The invention relates to a method that can be applied instead of LDL-C measurement for the clinical diagnosis of cardiovascular diseases or to assist in diagnosis.

[0004] State of the Art

[0005] In cardiovascular diseases (CVD), high low-density lipoprotein-cholesterol (LDL-C) concentration is directly associated with increased CVD mortality. Clinical studies demonstrated a strong and positive link between LDL-C concentration and the development and progression of CVD. Thus, LDL-C is considered to be an important marker for determining appropriate treatment strategies. However, the P-quantification (BQ) method, which is the reference method used for the measurement of this concentration, is not routinely preferred in clinical laboratories because it is costly, time-consuming, and challenging. In addition, its performance may be low at high triglyceride (TG) concentrations, and the measurement accuracy may vary in cases such as lipid disorders.

[0006] In order to overcome these difficulties, direct measurement methods developed as an alternative to BQ offer a more practical use in clinical laboratories because they are fast, economical and suitable for automation. In addition, these direct measurement methods stand out with their higher accuracy and are more advantageous compared to the formulas developed for approximately 30 LDL-C calculations. These developments offer a more effective and accessible way to determine LDL-C levels in clinical applications. Especially in developing countries, the Friedewald formula has been proposed to be used instead of P-quantification (BQ) and direct measurements (https: / / pubmed.ncbi.nlm.nih.gov / 4337382 / ). However, the formula's use of a constant coefficient decreased the accuracy of the LDL-C prediction value. The Martin / Hopkins formula (W02015069910A1), which was developed to overcome these limitations, used a variable coefficient instead of the constant coefficient used by the Friedewald Formula. The DeLong Formula, developed with an approach similar to the Friedewald Formula, offers an alternative solution to the limitations of the Friedewald formula by proposing different coefficients for the TG / VLDL-C ratio (https: / / pubmed.ncbi.nlm.nih.gov / 3469420 / ). In addition, the formulas produced by Rao, Anandaraja, Teerakanchana, Chen and Rasouli with multiple linear regression models (https: / / pubmed.ncbi.nlm.nih.gov / 3197296 / , https: / / www.internationaljournalofcardiology.com / article / S0167-5273(04)00458-9 / fulltext, https: / / pubmed.ncbi. nlm.nih.gov / 18426324 / , https: / / pubmed.ncbi.nlm.nih.gov / 20487572 / , https: / / pubmed.ncbi.nlm.nih.gov / 27595975 / ) were developed with a similar logic. In the study conducted in 1988, intermediate-density lipoprotein-cholesterol (IDL-C) was included in the LDL-C calculation formula and a new approach was proposed (Hattori Formula). In the study https: / / pubmed.ncbi.nlm.nih.gov / 15279333 / , the Puavillai formula derived from the Friedewald formula was introduced. The Puavili formula showed a high accuracy rate when the TG level was between 200-499 mg / dL. In 2008, the Ahmadi formula was developed for patients with TG levels less than 100 mg / dL based on lipid profiles obtained from the Iranian population; the Vujovic Formula, which was developed by excluding patients with TG levels greater than 400 mg / dL, was mentioned in (https: / / pubmed.ncbi.nlm.nih.gov / 18426324 / ). https: / / pubmed.ncbi.nlm.nih.gov / 20219094 / study. Formulations obtained from various geographies such as the Saiedullah formula (https: / / pubmed.ncbi.nlm.nih.gov / 26118159 / ) derived from lipid profiles measured in the Bangladesh population and the Balal formula (https: / / pubmed.ncbi.nlm.nih.gov / 20446783 / ) produced with the Turkish patient population are also used in LDL-C prediction. The Cordova formula was produced by ignoring TG levels (https: / / pubmed.ncbi.nlm.nih.gov / 23108766 / ), the Dansethakul formula was produced using pace regression (https: / / www.ncbi.nlm.nih.gov / pmc / articles / PMC4652637 / ), and the Lee& Hu formula was developed for individuals with total cholesterol levels between 100 and 300 mg / dL (https: / / pubmed.ncbi.nlm.nih.gov / 25816310 / ). The Rasouli Formula, produced in 2016, stood out with its high accuracy (https: / / pubmed.ncbi.nlm.nih.gov / 27595975 / ). This study revealed that the Rasouli formula has the lowest error rate compared to direct LDL-C measurements and the error levels of other formulas (Vojovic and Chen) are higher. When the Orejon, Ricra and Huallapa Formula, developed on the patient population in Peru, was stratified according to TG levels, it obtained more accurate LDL-C values compared to the Friedewald formula and it was observed that it had low analytical error values (http: / / www.scielo.org.pe / scielo.php?script=sci_arttext&pid=S1025-55832017000100007). This showed that the performance of the formula was more effective, especially at different TG levels.

[0007] The Roper Formula, specially produced for the pediatric population, was developed from lipid measurements of patients with TG levels equal to or greater than 150 mg / dL and TG less than 400 mg / dL (https: / / pubmed.ncbi.nlm.nih.gov / 28575159 / ) The Ghasemi Formula, in which measurements equal to or greater than TG 400 mg / dL were excluded, argued that the TG / VLDL-C ratio should change due to changes in TG level (https: / / pubmed.ncbi.nlm.nih.gov / 30043091 / ). The Ephraim formula proposed a 1 / 4 coefficient for the TG / VLDL-C ratio, stating that this ratio may vary depending on TG levels (https: / / pubmed.ncbi.nlm.nih.gov / 30693111 / ). In the study, it was observed that this formula had higher diagnostic accuracy than Friedewald formula and Anandaraja Formula. Focusing on hypertriglyceridemia due to chronic renal disease, the Bauer formula was developed assuming that it is not only associated with increased very low-density lipoprotein (VLDL) concentrations but also with increased TG content of VLDL particles (https: / / pubmed.ncbi.nlm.nih.gov / 33624033 / ). This formula provided a more specific evaluation, considering the content of triglycerides and VLDL, especially in individuals with chronic kidney disease.

[0008] The Gowda formula was derived using polynomial multiple regression analysis, and a new calculation method is proposed for the evaluation of lipid profiles in the study (https: / / journals.lww.com / kleu / Fulltext / 2019 / 12030 / Derivation_of_a_new_formula_for_the_estimation_of.7.aspx). The Caspian formula was created based on TG levels and developed with observations with TG less than 100 mg / dL, then confirmed with observations equal to or greater than TG 100 mg / dL (https: / / lipidworld.biomedcentral.com / articles / 10.1186 / sl2944-020-01306-7). In the study https: / / pubmed.ncbi.nlm.nih.gov / 32101259 / , the Sampson Formula, which was developed in 2020 to eliminate the limitations of other formulas whose performance decreased in cases where TG level was above 400 mg / dL, is mentioned. The Sampson formula was developed using three main components: 1) the linear contribution of the TG variable (related to the average VLDL-C lipid composition), 2) an interaction term for the cholesterol enrichment of VLDL-C with cholesterol ester transfer protein (CETP), and 3) a correction factor to account for the low cholesterol content of chylomicrons and LDL-C. It has been stated that this formula has a higher accuracy compared to the Friedewald formula or Martin / Hopkins Formula, especially for hypertriglyceridemic patients with a TG level between 400 and 800 mg / dL (https: / / www.sciencedirect.com / science / article / pii / S0021915023052851).

[0009] Finally, the Choi Formula, which was developed using linear multiple regression analysis in 2021, is presented on the link: https: / / pubmed.ncbi.nlm.nih.gov / 34544435 / . The validity of this formula was tested in three populations. BQ is performed at approximately 105,000×g at 10°C for 18 hours. While this procedure makes BQ exhausting and time-consuming, the fact that lipoproteins, which are highly unstable, are largely interchangeable by high salt concentrations and centrifugal forces makes their use routinely difficult. Furthermore, the use of a large number of different types of equipment and tubes makes it difficult to copy conditions from one laboratory to another, and consistent distinctions largely depend on the skill of the technician. On the other hand, it is very difficult to provide a complete and repeatable recovery. All homogeneous direct measurement methods have up-to-date certificates from CDC CRMLN (www.aacc.org / standards / cdc / kolesterolinfo.stm).

[0010] However, the consensus shown may not be valid for every version of the existing methods, differences from lot to lot, different calibrations made by distributors, different calibrations from country to country and reformulation of reagents affect the accuracy in individual laboratories (https: / / academic.oup.com / clinchem / article / 47 / 9 / 1579 / 5639318). Performance comparisons of all homogeneous methods were not made with the BQ method, and comparisons using variations of BQ protocols that could often give different results were also included. In addition, it was observed that there were few evaluations published, especially in peer-reviewed publications, for some reagents. The direct measurement method can predict LDL-C greater than it actually is at low LDL-C levels, which may cause patients to be classified into wrong categories. It was shown in the study https: / / academic.oup.com / ajcp / article / 148 / 1 / 42 / 386019 that direct LDL-C measurement is not suitable for pediatric populations. As a result, it is unclear whether LDL-C measured by homogeneous methods has any advantage over LDL-C measured by the BQ method. The Friedewald Formula, which is a calculation method, assumed a constant TG / VLDL-C ratio to predict the VLDL-C concentration. It has been shown in the studies https: / / journals.lww.com / mdjournal / fulltext / 2016 / 04050 / comparison_and_validation_of_10_equations.33.aspx, https: / / journals.plos.org / plosone / article?id=10.1371 / joumal. pone.0148147 that this constant 1 / 5 ratio is not valid at high TG levels. On the other hand, the formula requires fasting serum to accurately predict LDL-C; in case of not fasting, chylomicronemia leads to overestimation of VLDL-C and therefore underestimation of LDL-C. It has also been shown in the study https: / / cardiab.biomedcentral.com / articles / 10.1186 / 1475-2840-13-56 that it loses its accuracy at TG values above 150 mg / dL (1.69 mmol / L) and LDL-C levels below 70 mg / dL (1.8 mmol / L). These limitations have significant clinical implications. The incorrect determination of LDL-C can lead to incorrect classification of CVD risk and insufficient therapeutic intervention. Low high-density lipoprotein-cholesterol (HDL-C) levels can also affect VLDL-C estimates, leading to incorrect LDL-C results. In addition, TC measurement has the greatest effect on the variability in the calculation (https: / / pubmed.ncbi.nlm.nih.gov / 8330411 / ). Despite these disadvantages of the Friedewald method, LDL-C is still used for measurement in many hospitals around the world (https: / / www.ncbi.nlm.nih.gOv / pmc / articles / PMC10543427 / #ref9, https: / / link.springer.com / art icle / 10.1007 / sl2291-023-01142-3). Another calculation technique, the Martin / Hopkins formula, has been shown in a recent study, https: / / pubmed.ncbi.nlm.nih.gov / 30365923 / , to be unsuitable for patients with TG > 400 mg / dL and to overestimate LDL-C levels. LDL-C levels used in formula derivation were measured by Vertical Auto Profile (VAP) method. However, this method is a separation procedure based on the ultracentrifugation density and this procedure is not suitable for hyper triglyceridemic samples because TG-rich lipoproteins can adhere to the sides of the vertical centrifuge tubes. This possibility may lead to underestimation of VLDL-C levels (https: / / pubmed.ncbi.nlm.nih.gov / 32101259 / ). In the study https: / / journals.plos.org / plosone / article?id=10.1371 / journal.pone.0263860, it was stated that the performance of LDLC formulas changed from direct method to method and there was no stabilization. In addition, it was stated that the performances of the formulas used varied both with the change in the LDL-C, TG and nonHDL-C levels and according to the direct method used. The study, https: / / peerj.com / articles / 14544 / , compared the performance of different formulas in the pediatric population in different direct measurements and showed that the formulas did not have a stabilization. It has been emphasized that the reliability of the Delong formula is weakened by the increase in the TG level, just like the Friedewald formula (https: / / pubmed.ncbi.nlm.nih.gov / 2297909 / , https: / / pubmed.ncbi.nlm.nih.gov / 8131276 / ). Validation processes of the error formula could not be completed and validated in different populations. One of the disadvantages of the method is that the Rao formula is not standardized according to the standardization program of the Centers for Disease Control's Center (www.cdc.gov). The reliability of the Hattori formula is low at very low TC levels, when the TC level is greater than 348 mg / dL, and in the presence of hypertriglyceridemia. The validity of the Puavili formula is low, especially in dyslipidemic patient serums. The fact that the Anandaraja formula was produced only in the Indian patient group and that the formula was not validated in different racial and ethnic structures is one of the limitations of the formula. When the TG level exceeded 300 mg / dL, the performance of the Teerakanchana formula was weakened. The fact that the Ahmadi formula is produced only for patients with TG less than 100 mg / dL is one of the important limitations of the formula. In addition, in the study https: / / lipidworld.biomedcentral.com / articles / 10.1186 / s12944-020-01306-7, it was shown that the Ahmadi formula showed low accuracy even for patients with TG less than 100 mg / dL. The validity of the Saiedullah and Chen formula was not performed in different populations. Vujovic, Ephraim and Ghasemi formula was produced by excluding patients with TG level equal to or greater than 400 mg / dL. This is an indication that these formulas cannot be used when the TG level increases. The Balal formula was produced for patients with kidney transplant recipients and, just like the Vujovic Formula, it was not recommended for use in patients with a TG level greater than 400 mg / dL. In the study https: / / www.ncbi.nlm.nih.gov / pmc / articles / PMC4652637 / , the Cordova Formula's very low accuracy rate was mentioned. In the study https: / / www.ncbi.nlm.nih.gov / pmc / articles / PMC7595927 / , it was shown that the Dansethakul formula did not provide an improvement compared to the Friedewald Formula. The Lee& Hu formula performed worse than the Friedewald formula at concentrations lower than TC 100 mg / dL and greater than TC 300 mg / dL. The Bauer formula was not valid for other patient groups produced with lipid profiles of patients with a glomerular filtration rate less than 60 mL / min. It has been shown in their own studies that the performances of the Gowda and Caspian formula are lower than the performances of other formulas (https: / / journals.lww.com / kleu / Fulltext / 2019 / 12030 / Derivation_of_a_new_formula_for_the_estimation_of.7.aspx, https: / / lipidworld.biomedcentral.com / articles / 10.1186 / sl2944-020-01306-7). The Sampson formula predicts LDL-C as low (https: / / pubmed.ncbi.nlm.nih.gov / 36650044 / ). The Choi formula could not provide the desired performance in the three populations whose validity was questioned and could not show its validity in its own study. Said formulas were produced by taking into account the population of a single country. However, the study https: / / pubmed.ncbi.nlm.nih.gov / 34544435 / showed that the performance of the formulas differed even in the LDL-C estimation of patients living in rural and urban areas in the same country. Validation studies are ongoing in different populations for the routine use of the Martin / Hokins formula and Sampson formula (https: / / www. degruyter. com / document / doi / 10.1515 / cclm-2022- 1301 / html, https: / / jcp.bmj.com / content / early / 2023 / 06 / 20 / jcp-2023-208916.abstract). Patent application WO2015069910A1 focuses on a formula for LDL-C measurement. However, the formula described in this document has low prediction performance.

[0011] The formulas produced by traditional methods have various limitations, which can negatively affect the prediction accuracy.

[0012] Descriptions of the Figures Figure 1. A performance comparison of the new formula with known methods in different datasets of adult individuals.

[0013] Figure 2. A performance comparison of the new formula with known methods in different datasets of pediatric individuals.

[0014] Brief Description of the Invention

[0015] The method of the invention is a method that can be applied instead of clinical diagnosis of cardiovascular diseases or LDL-C measurement.

[0016] In developing countries, formulas developed for LDL-C prediction are used instead of device use for LDL-C measurement. The accuracy of these formulas is lower than the accuracy of the formula of the invention. The higher level of accuracy of the new formula can provide a significant advantage, especially in terms of early diagnosis and effective treatment of cardiovascular diseases. This situation can have a positive effect on the development of healthcare services and disease management at the global level.

[0017] Among the advantages of the new formula subject to the method of the invention, there is the opportunity to estimate LDL-C at a level close to direct measurement with total cholesterol (TC), high-density lipoprotein-cholesterol (HDL-C) and triglyceride (TG) lipid profiles measured from plasma. In this way, the need for costly direct measuring devices (for example, Roche, Beckman, etc.) will be eliminated and at the same time, the limitations of the Friedewald, Sampson and Martin / Hopkins formulas, which are widely used throughout the world, will be avoided. The new formula was tested in Roche, Siemens and Beckman direct measurement methods in the population of Korea, Tiirkiye, USA and Italy, and it was observed that it obtained higher accuracy than the existing equations (Figure 1). In addition, the new formula, which was tested in Roche, Siemens and Beckman measurement methods in the pediatric population of Tiirkiye, maintained the high accuracy rate compared to the equations (Figure 2). Thanks to the new formula, LDL-C levels of individuals of all ages, races and ethnicities can be accurately estimated. In the comparisons made, the new formula provides a great advantage to physicians by making the best prediction against the formulas whose performances change in the LDL-C, TG and nonHDL-C subgroups.

[0018] The new LDL-C formula developed provides higher accuracy compared to known methods. The performance of this new approach was successfully confirmed in the LDL-C measurements of 281866 individuals in a total of seven datasets obtained from three different populations. Due to the increasing emphasis on residual cardiovascular risk, especially in the case of high TG, accurate prediction of LDL-C is of clinical importance.

[0019] Detailed Description of the Invention

[0020] The invention describes a system and method for low-density lipoprotein-cholesterol (LDL-C) measurement. This system includes a storage unit in which the patient's lipid profiles (triglyceride (TG), total cholesterol (TC), high-density lipoprotein-cholesterol (HDL-C) values) measured within the scope of routine biochemistry tests are located, a calculation unit in which low-density lipoprotein-cholesterol (LDL-C) value is calculated using total-cholesterol (TC), total triglyceride (TG), high-density lipoprotein-cholesterol (HDL-C) and high-density non-lipoprotein-cholesterol (nonHDL-C) values, and a calculation processing unit in which coefficients

[0021]

[0022] andaredetermined if the patient's triglyceride (TG) level is less than 400 mg / dL and coefficient is determined if it is greater than 400 mg / dL. The mentioned coefficients are shown in equation 1 and equation 2.

[0023] The formula subject to the invention is presented in detail in equations 1 and 2. Table 1 and Table 2 to be used in the equation are given below. The coefficients in Table 1 were obtained from 24 multiple linear regression models in which the constant coefficient was not included, and the TG and nonHDL-C variables were accepted as independent variables. The TG and nonHDL-C cut-off points in the table were created by taking into account the Martin / Hopkins and Grundy studies (WO2015069910A1, https: / / www.jacc.org / doi / abs / 10.1016 / j.jacc.2018.11.002). The formulas developed for LDL-C prediction have accuracy problems, especially in hypertriglyceridemia where the TG level is 400 mg / dL and above (https: / / pubmed.ncbi.nlm.nih.gov / 32101259 / ). Hypertriglyceridemia causes an increase in small, dense LDL particles and a decrease in HDL-C levels, leading to atherogenic dyslipidemia as well as cardiovascular risks and the development of pancreatitis. In order to address these accuracy problems, the interaction term was added to the model by the CETP, as in the Sampson formula, which adds an interaction term for the cholesterol enrichment of VLDL-C (https: / / pubmed.ncbi.nlm.nih.gov / 32101259 / ). In addition, the individual contributions of the nonHDL-C and TG variables from the model were disabled. The coefficients (λ) obtained with the interaction term are given in Table 2. In the case of TG > 400 mg / dL, while the accepted cut-off points were used for the nonHDL-C categories, different cut-off points were tried for the TG categories and 400-499 mg / dL, 500-599 mg / dL and > 600 mg / dL cut-off points were used to ensure optimum performance. While creating the models, the logarithmic transformation was applied at the base of 10 due to the extreme right- skewed distributions of the nonHDL-C and TG variables. The Least Squares Method (LSM), which is the most commonly used method for predicting model parameters and aims to make the sum of error squares the smallest, was preferred (https: / / books.google.com.tr / books / about / Applied_Regression_Analysis_Linear_Model.html? id=pr2mKvAxXeYC&redir_esc=y,

[0024] https: / /

[0025]

[0026] books, gppgle.cotrLtr / bppks / abp^^ gAACAAJ&redir_esc=y).

[0027]

[0028] LDL − C = TC − HDL − antilog₁₀((β₁×log₁₀(TG)) + β₂×log₁₀(nonHDL)) (Equation 1) LDL − C = TC − HDL − antilog₁₀(log₁₀(TG))×log₁₀(nonHDL)×λ) (Equation 2) First, the measurement of TG, TC, and HDL-C levels, also known as the patient's lipid panel, is performed within the scope of routine biochemistry tests. According to the measurement results, if the TG level is below 400 mg / dL, the coefficients in Tablel

[0029]

[0030] and fib)areused; however, if the TG level is above 400 mg / dL, the coefficients given in Table2 ( ) preferred) are used. The nonHDL-C value is calculated by subtracting the HDL-C value from the total cholesterol (TC) value. Then, it is determined which cell to use according to TG and high- density non-lipoprotein-cholesterol (nonHDL-C) values. Finally, the LDL-C value is calculated by replacing the TC, HDL-C, nonHDL-C and TG values in equation 1 or 2.

[0031] Table 1. TG <400 mg / dL

[0032] TG nonHDL-C

[0033] <100 100-130 130-160 160-190 190-220 >220

[0034] <100 0.442; 0.18 0.364; 0.252 0.347; 0.265 0.485; 0.16 0.228; 0.368 0.395;

[0035] 0.246

[0036] 100- 0.874; -0.264 0.7; -0.071 0.571; 0.07 0.711; -0.052 0.619; 0.045 0.18; 0.466 150

[0037] 150- 0.793; -0.191 0.759; -0.132 0.665; -0.016 0.493; 0.167 0.957; -0.265 0.334;

[0038]

[0039] 200 0.342

[0040] 200- 0.71; -0.091 0.754; -0.123 0.836; -0.194 0.866; -0.207 0.855; -0.179 0.765; - 400 0.066

[0041]

[0042] For example, if TG<100 and the nonHDL-C value is <100

[0043]

[0044] and β₂ are 0.442; 0.18, respectively.

[0045] Table 2. IfTG> 400

[0046] TG nonHDL-C

[0047] <100 100-130 130-160 160-190 190-220 >220

[0048] 400-500 0.300 0.305 0.297 0.291 0.286 0.283

[0049] 500-600 0.306 0.314 0.303 0.297 0.295 0.289

[0050] >600 0.245 0.300 0.303 0.299 0.297 0.296

[0051]

[0052] For example, if TG > 400-500 and the nonHDL-C value is <100, X. is 0.300.

[0053] Lipid profiles were used with direct measurements obtained from the Korea-Roche population for the development of the formula of the invention. The performance of the new formula was tested in Korea-Roche with lipid profiles of 20,334 people, Italy-Beckman with lipid profiles of 111,938 people, Tiirkiye-Roche with lipid profiles of 119,884 people, Turkiye-Beckman with lipid profiles of 30,087 people, Tiirkiye-Siemens with lipid profiles of 19,298 people, pediatric Tiirkiye-Roche with 2,356 people, pediatric Tiirkiye-Siemens with 659 people and pediatric Tiirkiye-Beckman with 893 people. In this way, the validity of the invention was ensured in different races, ages and direct measurement devices. This is an important feature that distinguishes the invention from other formulas. Because the existing formulas were generally tested on a single population and a single measurement method, their overall validity was not achieved. In addition, the evaluation of the invention completely in external test sets and obtaining high performance analysis results provide solid evidence on the general validity of the invention (https: / / pubmed.ncbi.nlm.nih.gov / 33294870 / ).

[0054] The sample application of the LDL-C estimate can be explained by the following scenario: For the calculation of LDL-C level, the blood sample taken from the individual is transmitted to the laboratory and total cholesterol (TC), high-density lipoprotein-cholesterol (HDL-C) and triglyceride (TG) levels in plasma are measured. The obtained lipid profiles are written in the new formula using a computer, workstation, smartphone or a simple calculator. As a result of this process, LDL-C results of the patient are obtained.

Claims

CLAIMS1. A system for low-density lipoprotein-cholesterol (LDL-C) measurement, characterized in comprising:• a storage unit containing the patient's lipid profiles (triglyceride (TG), total cholesterol (TC), high-density lipoprotein-cholesterol (HDL-C) values) measured within the scope of routine biochemistry tests,• a calculation unit that uses total cholesterol (TC), total triglyceride (TG), high- density lipoprotein-cholesterol (HDL-C) and high-density non-lipoprotein- cholesterol (nonHDL-C) values to calculate low-density lipoprotein- cholesterol (LDL-C) values,• a calculation processing unit in which theand2coefficients are determined if the patient's triglyceride (TG) level is less than 400 mg / dL, and the coefficient is determined if it is greater than 400 mg / dL,using the formulaLDL — C — TC — HDL — antUogi-Q( f>1xlogiQ{TG ) 4-,xZo$10(nonHDL)) or LDL — C = TC — HDL — antiIo^18(io510(TG))xiaig10(nonffDL)xX.).

2. A method of operation of the system according to claim 1, characterized in that it comprises the following process steps:• calculating high-density non-lipoprotein-cholesterol (nonHDL-C) value by calculation unit by subtracting high-density lipoprotein-cholesterol (HDL-C) value from total cholesterol (TC) value,• calculating total cholesterol (TC), high-density lipoprotein-cholesterol (HDL- C), high-density non-lipoprotein-cholesterol (nonHDL-C) and total triglyceride (TG) values and low-density lipoprotein-cholesterol (LDL-C) value by the calculation unit.

3. A method according to claim 2, characterized in that the (LDL-C) value is calculated using equation 1 if the total triglyceride (TG) level is below 400 mg / dL.LDL -K = TC — HDL — antiio5i0((pixio510(Tff)) 4- p,xio5i0(non#£>£)) (Equation 1)4. A method according to claim 3, characterized in that the coefficients 0.442 ( ) and 0.18 (p9) are used if the total triglyceride (TG) level is less than 100 mg / dL and the nonHDL-C value is less than 100.

5. A method according to claim 3, characterized in that the coefficients 0.364 (p ) and 0.252 (p7) are used if the total triglyceride (TG) level is less than 100 mg / dL and the nonHDL-C value is between 100 and 130.

6. A method according to claim 3, characterized in that the coefficients 0.347 (p ) and 0.265 (p,) are used if the total triglyceride (TG) level is less than 100 mg / dL and the nonHDL-C value is between 130 and 160.

7. A method according to claim 3, characterized in that the coefficients 0.485 ( ) and 0.16 (9) are used if the total triglyceride (TG) level is less than 100 mg / dL and the nonHDL-C value is between 160 and 190.

8. A method according to claim 3, characterized in that the coefficients 0.228 (p ) and 0.368 (p7) are used if the total triglyceride (TG) level is less than 100 mg / dL and the nonHDL-C value is between 190 and 220.

9. A method according to claim 3, characterized in that the coefficients 0.395 (p ) and 0.246 (,) are used if the total triglyceride (TG) level is less than 100 mg / dL and the nonHDL-C value is greater than 220.

10. A method according to claim 3, characterized in that the coefficients 0.874 (p ) and - 0.264 (p?) are used if the total triglyceride (TG) level is between 100 mg / dL and 150 mg / dL and the nonHDL-C value is less than 100.

11. A method according to claim 3, characterized in that the coefficients 0.7 (p ) and - 0.071 (p,) are used if the total triglyceride (TG) level is between 100 mg / dL and 150 mg / dL and the nonHDL-C value is between 100 and 130.

12. A method according to claim 3, characterized in that the coefficients 0.571 (p ) and 0.07 (p,) are used if the total triglyceride (TG) level is between 100 mg / dL and 150 mg / dL and the nonHDL-C value is between 130 and 160.

13. A method according to claim 3, characterized in that the coefficients 0.711 (p ) and - 0.052 (P2) are used if the total triglyceride (TG) level is between 100 mg / dL and 150 mg / dL and the nonHDL-C value is between 160 and 190.

14. A method according to claim 3, characterized in that the coefficients 0.619 (p ) and 0.045 (p_.) are used if the total triglyceride (TG) level is between 100 mg / dL and 150 mg / dL and the nonHDL-C value is between 190 and 220.

15. A method according to claim 3, characterized in that the coefficients 0.18 (p ) and 0.466 (p7) are used if the total triglyceride (TG) level is between 100 mg / dL and 150 mg / dL and the nonHDL-C value is greater than 220.

16. A method according to claim 3, characterized in that the coefficients 0.793 (p ) and - 0.191 (p,) are used if the total triglyceride (TG) level is between 150 mg / dL and 200 mg / dL and the nonHDL-C value is less than 100.

17. A method according to claim 3, characterized in that the coefficients 0.759 (p ) and - 0.132 (p_.) are used if the total triglyceride (TG) level is between 150 mg / dL and 200 mg / dL and the nonHDL-C value is between 100 and 130.

18. A method according to claim 3, characterized in that the coefficients 0.665 ( ) and - 0.016 (p7) are used if the total triglyceride (TG) level is between 150 mg / dL and 200 mg / dL and the nonHDL-C value is between 130 and 160.

19. A method according to claim 3, characterized in that the coefficients 0.493 (p ) and 0.167 (p,) are used if the total triglyceride (TG) level is between 150 mg / dL and 200 mg / dL and the nonHDL-C value is between 160 and 190.

20. A method according to claim 3, characterized in that the coefficients 0.957 (p ) and - 0.265 (p?) are used if the total triglyceride (TG) level is between 150 mg / dL and 200 mg / dL and the nonHDL-C value is between 190 and 220.

21. A method according to claim 3, characterized in that the coefficients 0.334 (p ) and 0.342 (p,) are used if the total triglyceride (TG) level is between 150 mg / dL and 200 mg / dL and the nonHDL-C value is greater than 220.

22. A method according to claim 3, characterized in that the coefficients 0.71 (p ) and - 0.091 (p,) are used if the total triglyceride (TG) level is between 200 mg / dL and 400 mg / dL and the nonHDL-C value is less than 100.

23. A method according to claim 3, characterized in that the coefficients 0.754 (p ) and - 0.123 (P2) are used if the total triglyceride (TG) level is between 200 mg / dL and 400 mg / dL and the nonHDL-C value is between 100 and 130.

24. A method according to claim 3, characterized in that the coefficients 0.836 (p ) and - 0.194 (p_.) are used if the total triglyceride (TG) level is between 200 mg / dL and 400 mg / dL and the nonHDL-C value is between 130 and 160.

25. A method according to claim 3, characterized in that the coefficients 0.866 ( ) and - 0.207 (p7) are used if the total triglyceride (TG) level is between 200 mg / dL and 400 mg / dL and the nonHDL-C value is between 160 and 190.

26. A method according to claim 3, characterized in that the coefficients 0.855 (|3 ) and - 0.179 (p,) are used if the total triglyceride (TG) level is between 200 mg / dL and 400 mg / dL and the nonHDL-C value is between 190 and 220.

27. A method according to claim 3, characterized in that the coefficients 0.765 (p ) and - 0.066 (p_.) are used if the total triglyceride (TG) level is between 200 mg / dL and 400 mg / dL and the nonHDL-C value is greater than 200.

28. A method according to claim 2, characterized in that the (LDL-C) value is calculated using equation 2 if the total triglyceride (TG) level is above 400 mg / dL.LDL — K = TC — HDL — (Equation 2)29. A method according to claim 28, characterized in that the coefficient 0.300 (1) is used if the total triglyceride (TG) level is between 400 mg / dL and 500 mg / dL and the nonHDL-C value is less than 100.

30. A method according to claim 28, characterized in that the coefficient 0.305 (A) is used if the total triglyceride (TG) level is between 400 mg / dL and 500 mg / dL and the nonHDL-C value is between 100 and 130.

31. A method according to claim 28, characterized in that the coefficient 0.297 (1) is used if the total triglyceride (TG) level is between 400 mg / dL and 500 mg / dL and the nonHDL-C value is between 130 and 160.

32. A method according to claim 28, characterized in that the coefficient 0.291 (X) is used if the total triglyceride (TG) level is between 400 mg / dL and 500 mg / dL and the nonHDL-C value is between 160 and 190.

33. A method according to claim 28, characterized in that the coefficient 0.286 (A) is used if the total triglyceride (TG) level is between 400 mg / dL and 500 mg / dL and the nonHDL-C value is between 190 and 220.

34. A method according to claim 28, characterized in that the coefficient 0.283 (A) is used if the total triglyceride (TG) level is between 400 mg / dL and 500 mg / dL and the nonHDL-C value is greater than 220.

35. A method according to claim 28, characterized in that the coefficient 0.306 (X) is used if the total triglyceride (TG) level is between 500 mg / dL and 600 mg / dL and the nonHDL-C value is less than 100.

36. A method according to claim 28, characterized in that the coefficient 0.314 (X) is used if the total triglyceride (TG) level is between 500 mg / dL and 600 mg / dL and the nonHDL-C value is between 100 and 130.

37. A method according to claim 28, characterized in that the coefficient 0.303 ( ) is used if the total triglyceride (TG) level is between 500 mg / dL and 600 mg / dL and the nonHDL-C value is between 130 and 160.

38. A method according to claim 28, characterized in that the coefficient 0.297 (X.) is used if the total triglyceride (TG) level is between 500 mg / dL and 600 mg / dL and the nonHDL-C value is between 160 and 190.

39. A method according to claim 28, characterized in that the coefficient 0.295 (X) is used if the total triglyceride (TG) level is between 500 mg / dL and 600 mg / dL and the nonHDL-C value is between 190 and 220.

40. A method according to claim 28, characterized in that the coefficient 0.289 (A) is used if the total triglyceride (TG) level is between 500 mg / dL and 600 mg / dL and the nonHDL-C value is greater than 220.

41. A method according to claim 28, characterized in that the coefficient 0.245 ( ) is used if the total triglyceride (TG) level is greater than 600 mg / dL and the nonHDL-C value is less than 100.

42. A method according to claim 28, characterized in that the coefficient 0.300 (X) is used if the total triglyceride (TG) level is greater than 600 mg / dL and the nonHDL-C value is between 100 and 130.

43. A method according to claim 28, characterized in that the coefficient 0.303 (X) is used if the total triglyceride (TG) level is greater than 600 mg / dL and the nonHDL-C value is between 130 and 160.

44. A method according to claim 28, characterized in that the coefficient 0.299 (X) is used if the total triglyceride (TG) level is greater than 600 mg / dL and the nonHDL-C value is between 160 and 190.

45. A method according to claim 28, characterized in that the coefficient 0.297 ( ) is used if the total triglyceride (TG) level is greater than 600 mg / dL and the nonHDL-C value is between 190 and 220.

46. A method according to claim 28, characterized in that the coefficient 0.296 (.) is used if the total triglyceride (TG) level is greater than 600 mg / dL and the nonHDL-C value is greater than 220.

47. A device, characterized in that it comprises a system according to claim 1.

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