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... all above TG levels studied, mean LDL-C calculated by using Puavillai formula (107.9 mg/dL) showed a mean difference of -4.8 mg/dL when compared to mean LDL-C value measured directly (103.1 mg/dL). It showed better statistically significant correlation with mean Direct LDL-C value, as compared to other formulae (r 2 0.8119, p <0.001) (Table 6): Discussion LDL-Cholesterol concentration in blood has positive correlation with coronary heart diseases like atherosclerosis. This is due to deposition of LDL- Cholesterol in tissues and endothelial spaces of arteries like coronaries. ...
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... [13] In another study by Nishtha Wadhwa [14] et al., it was concluded that in Indian Population, Vujovic formula appears to be more accurate than any other formula. Whereas in another study conducted by Mugdha Dilip Garule [15] et al, it was reported that, Puavillai formula is the most accurate formula to calculate LDL-C at TG levels up to 150 mg/dL and also at all TG levels studied whereas Friedewald's formula is the best at TG levels between 151 to 199 mg/dL and Anandaraja formula at TG 200 to 399 mg/dL. However in the present when the comparison was done even at different levels of LDL-C (ie optimal level, desirable level, borderline and high-risk level), calculated LDL-C using Freidewald formula did not show significant difference whereas the other formulae showed significant difference with Ahmadi formula overestimating and others formulae the underestimating the LDL-C values at all levels of LDL-C as shown in table 4. ...
... The results showed that Puavillai formula estimate LDL-C with high accuracy in subjects with high level of TG in the Iranian population. In this regard, Garule et al. concluded that the Puavillai formula is the most accurate formula and correlates with the direct method at all TG levels [27]. It was inferred from the results that the Friedewaldestimated LDL-C was 0.21 mmol/L higher than the directly measured LDL-C at TG levels of <0.56 mmol/L, while for TG > 4.51 mmol/L, mean value of the Freidewald-calculated LDL-C was approximately 0.52 mmol/L lower than the direct LDL-C. ...
Background:
Considering the crucial role of low-density lipoprotein-cholesterol (LDL-C) concentration in determining cardiovascular risk, the accuracy of LDL-C estimation is essential. To date, various types of formulae have been introduced, albeit their accuracy has not been assessed in varied populations. In this study, the accuracy of eight formulae for LDL-C estimation was evaluated in an Iranian population.
Methods:
A data set of 2752 individuals was included in the study and all samples were analyzed in term of lipid profiles using direct homogeneous assay. The population was divided into various subgroups based on the triglyceride (TG), high-density lipoprotein- cholesterol (HDL-C), total cholesterol (TC), fasting blood sugar (FBS) and age values and estimated LDL-C values by Friedewald, Chen, de Cordova, Vujovic, Anandaraja, Hattori, Ahmadi, and Puavillai equations were compared to the directly measured LDL-C in each subgroup.
Results:
Estimated LDL-C values by Puavillai formulae showed an insignificant difference compared to the directly measured LDL-C in subjects with high level of TG. However, for TG range < 3.38 mmol/L and high levels of HDL-C, the difference between the means of estimated LDL-C by Hattori and de Cordova formulas, and directly measured LDL-C was relatively lower than other equations. In addition, estimated LDL-C by Hattori and de Cordova formulae had insignificant differences as compared to the direct LDL-C at some levels of cholesterol, the normal level of FBS and some age ranges.
Conclusions:
Therefore, it seems that Hattori and de Cordova formulas can be considered as the best alternatives for LDL-C direct measurement in the Iranian population, especially for healthy subjects.
Introduction
Assessing LDL cholesterol is pivotal for cardiovascular risk evaluation. While direct LDL measurement is accurate, calculated LDL methods offer practicality and cost-effectiveness. This study aims to evaluate the correlation between direct LDL measurement and various calculated LDL methods, shedding light on their clinical utility.
Methods
A retrospective analysis of lipid profiles from 1075 patients was conducted, encompassing direct LDL measurement and calculation of LDL using nine different methods. Statistical analyses, including correlation coefficients and scatter plots, were employed to assess the agreement between direct LDL and calculated LDL methods.
Results
Surprisingly, all calculated LDL methods exhibited a robust correlation with direct LDL measurement across the study cohort. The Friedewald equation, as well as modified equations demonstrated particularly robust correlations. These findings indicate the reliability of calculated LDL methods in estimating LDL cholesterol levels.
Discussion
The significant correlation observed between direct LDL measurement and calculated LDL methods underscores the clinical utility of the latter. While direct LDL measurement remains the gold standard, calculated LDL methods offer practical advantages, particularly in resource-limited settings.
Conclusion
In conclusion, this study highlights the excellent correlation between direct LDL measurement and calculated LDL methods in lipid profile assessment. Clinicians can leverage calculated LDL methods as reliable alternatives for LDL cholesterol estimation, facilitating efficient cardiovascular risk evaluation in routine clinical practice. Further research may explore the optimal use of calculated LDL methods in specific patient populations, enhancing their clinical applicability and utility.
