EISSN: 2980-0749
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2021, Cilt 19, Sayı 1, Sayfa(lar) 022-031
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Martin Hopkins and Friedewald Calculation with Direct LDL-C Measurement: Evaluation with RCV
Erdem Çokluk1, Mehmet Ramazan ŞEKEROĞLU1, Fatıma Betül TUNCER1 M. Ramazan Akdemir2
1Sakarya Üniversitesi Tip Fakültesi, Tibbi Biyokimya Anabilim Dali, Sakarya, Türkiye
2Sakarya Üniversitesi Tip Fakültesi, Kardiyoloji Anabilim Dali, Sakarya, Türkiye
Keywords: LDL Cholesterol; Martin / Hopkins Formula; Friedewald formula; Reference Change Value; Lipid parameters; Optimal test order frequency

Objective: In the study, it was aimed to determine the harmony of LDL-C levels determined by enzymatic(direct) and computational method, to have an idea about the optimal request frequency by examining the significance of the percentage changes of repeated LDL-C measurements according to the reference change value(RCV).

Materials and Methods: Results of a total of 179 individuals aged 18-65, whose lipid profiles were analyzed twice in a year, were obtained from the laboratory information management system. The relationship between the measured LDL-C levels and the LDL-C levels calculated by Martin/Hopkins and Friedewald formulas was examined. Bland-Altman analysis was used to compare the results. In addition, the percentage changes of repeated LDL-C results was compared with the calculated RCV were evaluated.

Results: Both computational LDL-C levels were lower than direct measurement. Although the correlation of direct and computational methods was found to be high, the mean of the differences was found to be higher than the %RCV calculated for LDL in Blant Altman analysis. The change in the repeated measurements of those with the first LDL-C result above 130mg/dL in direct measurement and above 160mg/dL in the Fridewald calculation was significant compared to the RCV%.

Conclusion: While presenting the LDL-C result, we believe that the same method should be used in monitoring LDL-C in order to avoid errors due to variations between methods. The effect of analytical and biological variations on measurement results should also be taken into account while evaluating the variation between results. Thus, unnecessary tests, misdiagnoses and treatments can be avoided.


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