THE CALCULATION MEASUREMENT UNCERTAINTY OF GLUCOSE IN BLOOD GAS ANALYZER AND AUTOMATED ANALYZER.

Autor: Çalık, Gizem Yılmaz, Çolak, Emel, Haskılıç, Yunus Emre, Ibiş, Oğulcan, Şeneş, Mehmet, Yücel, Doğan
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Zdroj: Turkish Journal of Biochemistry / Turk Biyokimya Dergisi; 2019 Supplement, Vol. 44, p46-47, 2p
Abstrakt: Objectives: In this study, our aim is to calculate glucose measurement uncertainty and total error in blood gas analyzer and automated analyser used in our hospital. Materials and Methods: The measurement uncertainty for glucose between August 2018 and January 2019 was calculated on the ABL Radiometer Flex 800 blood gas analyzer and the Roche Cobas 6000 automated analyzer. The top-down calculation model consisting of six stages based on the Guideline for Measurement Uncertainty in Medical Laboratories and NordTest NT TR 537 instructions were used. In this calculation, internal quality control and external quality assessment data were used within the same 6 months. The total error (TE)= %bias+(1. 65x %CV) formula was used. These values were compared with the total allowable error (% TEa) values obtained from the biological variation data of CLIA (10%), Rilibak (15%) and Fraser (7. 9%). Results: Glucose measurement uncertainty was found as 7. 73% in blood gas analyzer and 9. 4% in automated analyser. Total analytical error values were found as 11. 75% and 6. 42% in blood gas analyzer and automated analyser, respectively. The measurement uncertainty for the blood gas analyzer was lower than all of the TEa values, and the total error was found to exceed the CLIA and Fraser % TEa values. The measurement uncertainty for the automated analyser is higher than the Fraser % TEa, lower than the others, and the total error is lower than all the TEa values. Conclusion: In our study, the analytical performance of the glucose test performed on the blood gas analyzer and the automated analyser was found to be sufficient. In order to interpret the test results more accurately, laboratories should calculate the measurement uncertainty for each parameter and present the results in a way not to exceed the target TEA values. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index