Determining a new formula for calculating low-density lipoprotein cholesterol: data mining approach

Dansethakul, Prabhop; Thapanathamchai, Lalin; Saichanma, Sarawut; Worachartcheewan, Apilak; Pidetcha, Phannee

doi:10.17179/excli2015-162

Cited by 14 publications

(6 citation statements)

References 14 publications

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“…Many LDL-C equations besides the Friedewald equation have been described, but most are not significantly better than the Friedewald equation compared with the β-quantification reference method, a swinging-bucket ultracentrifugation precipitation-based procedure. Recently, Martin et al developed an equation (hereafter referred to as the Martin equation) based on the Vertical Auto Profile test, which is a vertical-rotor ultracentrifugation-based method .…”

Section: Introductionmentioning

confidence: 99%

“…2 Although tests for directly measuring LDL-C (dLDL-C) have been developed, it is still common practice to calculate LDL-C because of the extra cost of adding dLDL-C to the lipid panel and the poor analytical performance of some dLDL-C tests. [3][4][5][6] Many LDL-C equations besides the Friedewald equation have been described, [7][8][9][10][11][12][13][14][15][16][17][18][19][20] but most are not significantly better than the Friedewald equation compared with the β-quantification reference method, a swinging-bucket ultracentrifugation precipitation-based procedure. Recently, Martin et al 21,22 developed an equation (hereafter referred to as the Martin equation) based on the Vertical Auto Profile test, which is a vertical-rotor ultracentrifugation-based method.…”

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confidence: 99%

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A New Equation for Calculation of Low-Density Lipoprotein Cholesterol in Patients With Normolipidemia and/or Hypertriglyceridemia

et al. 2020

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IMPORTANCE Low-density lipoprotein cholesterol (LDL-C), a key cardiovascular disease marker, is often estimated by the Friedewald or Martin equation, but calculating LDL-C is less accurate in patients with a low LDL-C level or hypertriglyceridemia (triglyceride [TG] levels Ն400 mg/dL). OBJECTIVE To design a more accurate LDL-C equation for patients with a low LDL-C level and/or hypertriglyceridemia. DESIGN, SETTING, AND PARTICIPANTS Data on LDL-C levels and other lipid measures from 8656 patients seen at the National Institutes of Health Clinical Center between January 1, 1976, and June 2, 1999, were analyzed by the β-quantification reference method (18 715 LDL-C test results) and were randomly divided into equally sized training and validation data sets. Using TG and non-high-density lipoprotein cholesterol as independent variables, multiple least squares regression was used to develop an equation for very low-density lipoprotein cholesterol, which was then used in a second equation for LDL-C. Equations were tested against the internal validation data set and multiple external data sets of either β-quantification LDL-C results (n = 28 891) or direct LDL-C test results (n = 252 888). Statistical analysis was performed from August 7, 2018, to July 18, 2019. MAIN OUTCOMES AND MEASURES Concordance between calculated and measured LDL-C levels by β-quantification, as assessed by various measures of test accuracy (correlation coefficient [R 2 ], root mean square error [RMSE], mean absolute difference [MAD]), and percentage of patients misclassified at LDL-C treatment thresholds of 70, 100, and 190 mg/dL. RESULTSCompared with β-quantification, the new equation was more accurate than other LDL-C equations (slope, 0.964; RMSE = 15.2 mg/dL; R 2 = 0.9648; vs Friedewald equation: slope, 1.056; RMSE = 32 mg/dL; R 2 = 0.8808; vs Martin equation: slope, 0.945; RMSE = 25.7 mg/dL; R 2 = 0.9022), particularly for patients with hypertriglyceridemia (MAD = 24.9 mg/dL; vs Friedewald equation: MAD = 56.4 mg/dL; vs Martin equation: MAD = 44.8 mg/dL). The new equation calculates the LDL-C level in patients with TG levels up to 800 mg/dL as accurately as the Friedewald equation does for TG levels less than 400 mg/dL and was associated with 35% fewer misclassifications when patients with hypertriglyceridemia (TG levels, 400-800 mg/dL) were categorized into different LDL-C treatment groups. CONCLUSIONS AND RELEVANCEThe new equation can be readily implemented by clinical laboratories with no additional costs compared with the standard lipid panel. It will allow for more accurate calculation of LDL-C level in patients with low LDL-C levels and/or hypertriglyceridemia (TG levels, Յ800 mg/dL) and thus should improve the use of LDL-C level in cardiovascular disease risk management.

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Section: Introductionmentioning

confidence: 99%

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confidence: 99%

A New Equation for Calculation of Low-Density Lipoprotein Cholesterol in Patients With Normolipidemia and/or Hypertriglyceridemia

et al. 2020

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“…The serum levels of glucose, total cholesterol, triglyceride, high-density lipoprotein cholesterol (HDL-c), creatinine, and blood urea nitrogen (BUN) were measured using enzymatic colorimetric methods (Pars Azmoon Co., Tehran, Iran) [ 27 ]. The level of low-density lipoprotein cholesterol (LDL-c) was calculated using the Friedewald formula for samples with a concentration of less than 400 mg/dL of triglyceride [ 28 ]. The serum level of insulin was also measured using the enzyme-linked immunosorbent assay (ELISA) kit for rats (Crystal Chem.…”

Section: Methodsmentioning

confidence: 99%

L-Lysine Ameliorates Diabetic Nephropathy in Rats with Streptozotocin-Induced Diabetes Mellitus

Jozi

Kheiripour

Taheri

et al. 2022

BioMed Research International

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Introduction. Diabetic nephropathy is one of the leading causes of end-stage renal disease worldwide. Uncontrolled hyperglycemia and subsequent production of glycation end-products activate the paths which lead to diabetic nephropathy. The aim of this study was to assess the effects of L-lysine on antioxidant capacity, biochemical factors, kidney function, HSP70 level, and the expression of the TGFβ, VEGF, and RAGE genes in rats with streptozocin-induced diabetes mellitus. Methods. Thirty-two male Wistar rats were randomly allocated to four eight-rat groups, namely, a healthy group, a diabetic group treated with vehicle (DM + vehicle), a diabetic group treated with L-lysine (DM + Lys), and a healthy group treated with L-lysine (healthy + Lys). Rats in the DM + Lys and the healthy + Lys groups were treated with L-lysine 0.15%. The levels of fasting blood glucose, insulin, HbA1C, advanced glycation end-products (AGEs), lipid profile, serum creatinine, blood urea nitrogen, glomerular filtration rate, urine microalbumin, oxidative stress parameters, kidney histology and morphology, and TGFβ, VEGF, and RAGE gene expressions were assessed. Findings. An eight-week treatment with L-lysine significantly reduced the levels of fasting blood glucose, AGEs, kidney function parameters, oxidative stress parameters, lipid profile, and the TGFβ, VEGF, and RAGE gene expression and significantly increased the levels of serum insulin and tissue HSP70. Conclusion. Treatment with L-lysine seems to slow down the progression of diabetic nephropathy.

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“…Total cholesterol, triglycerides, and high-density lipoprotein cholesterol (HDL-C) were determined using enzymatic, GPO-trinder, and direct methods, respectively. Low-density lipoprotein cholesterol (LDL-C) was calculated based on total cholesterol and HDL-C levels (Dansethakul, Thapanathamchai, Saichanma, Worachartcheewan, & Pidetcha, 2015). Alanine aminotransferase (ALT) levels were assessed with modified IFCC method.…”

Section: Clinical Assessmentsmentioning

confidence: 99%

Combined high‐intensity interval training as an obesity‐management strategy for adolescents

Videira-Silva

Hetherington‐Rauth

Sardinha

et al. 2021

European Journal of Sport Science

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Effective and safe exercise protocols for obesity management in adolescents are imperative. This study aimed to analyse compliance, efficacy, and safety of combined high-intensity interval training circuit (HIIT) in the management of obesity (including overweight) in adolescents, compared to traditional training (TT). Data from 55 adolescents (47.3% girls) (TT n = 31; HIIT n = 24), aged 12-18 (mean age of 14.3 ± 1.7), with overweight and obesity (median BMI z-score of 2.95), were assessed at baseline and month 6 (Clinicaltrials.gov/NCT02941770). During the 6-month intervention, participants in both exercise groups attended two exercise sessions/week (60 min/session) along with a set of appointments with a paediatrician, nutritionist, and exercise physiologist. Forty-six participants completed the intervention (TT n = 23; HIIT n = 23). Exercise session attendance (≥80%) was significantly higher among HIIT participants (73.9 vs. 13.0%, p < .001). HIIT, but not TT, showed a significant decrease in BMI z-score (d = 0.40, p < .001), body fat mass (BFM, %) (d = 0.41, p = .001), and trunk fat mass (d = 0.56, p < .001), as well as a significant increase in muscle mass (MM, %) (d = 0.28, p = .001) between baseline and 6 months. According to generalized estimating equations, time-byattendance interactions (instead of time-by group) were found in BMI z-score (β = 0.25, 95%CI: 0.17, 0.33), BFM (β = 2.29, 95%CI: 1.02, 3.56), trunk fat mass (β = 2.94, 95%CI: 1.70, 4.18), and MM (β = −1.16, 95%CI: −1.87, −0.45). No adverse events were reported during HIIT sessions. Although compliance may mediate the impact of an exercise protocol on health-related outcomes, HIIT showed to be safe, with higher compliance compared to TT, which may result in improved outcomes overtime.

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Determining a new formula for calculating low-density lipoprotein cholesterol: data mining approach

Cited by 14 publications

References 14 publications

A New Equation for Calculation of Low-Density Lipoprotein Cholesterol in Patients With Normolipidemia and/or Hypertriglyceridemia

A New Equation for Calculation of Low-Density Lipoprotein Cholesterol in Patients With Normolipidemia and/or Hypertriglyceridemia

L-Lysine Ameliorates Diabetic Nephropathy in Rats with Streptozotocin-Induced Diabetes Mellitus

Combined high‐intensity interval training as an obesity‐management strategy for adolescents

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