The effect of repeated measures on the accuracy of antithrombin III activity assessment using chromogenic assay: 616.151.55

Abstract

Summary. Introduction. Increasing statistical power in determining the functional activity of antithrombin III (АТ) broadens the scope for its use as a criterion indicator of hemostasis and a prognostic marker, thereby reducing the probability of false rejection of one or another hypothesis. Aim: to assess the effect of increasing the number of repeated measures on the accuracy of АТ activity assessment using the chromogenic method based on the amidolytic activity of factor Xa. Materials and Methods. The study included seven-fold measurements of AT activity in human plasma samples, which demonstrated consistent results within each of the four analyzed groups and were obtained from whole blood of donors. The parameter was measured for each biomaterial sample simultaneously and in parallel in ACL TOP 300 automatic coagulometer using HemosIL reagents. Three of the groups exhibited AT activity values within the reference range typical of adults, usually ranging from 80 to 120%, while one group demonstrated values that exceeded this range. Results. The coefficient of variation exhi- bited intra-series variability, ranging from 1.3 to 2.0% for the analyzed parameter across the four groups of samples. The impact of repeated measures was evaluated with a confidence level of 0.95 and 0.99. It was determined that the decrease in the size of the confidence interval when moving from two-fold to four-fold measurement on average is 81.1 and 93.1%, respectively. Furthermore, the decrease when moving from the fifth to the seventh measurement was found to be 22.7 and 28.8%. Conclusion. Although preanalytical work is highly automated and multiple measurements are repeatable, the recorded values of AT activity in identical samples can still differ by up to 8%. As the number of measurements of the parameter increases using the chromogenic method based on the amidolytic activity of factor Xa, the statistical power of the results decreases significantly after the fourth repeat.

For citation: Lemondzhava V. N., Sidorkevich S. V., Kasyanov A. D. The effect of repeated measures on the accuracy of antithrombin III activity assessment using chromogenic assay. Tromboz, gemostaz i reologiya. 2024;(4):46–52. (In Russ.).

References

1. Guria K., Guria G. T. Spatial aspects of blood coagulation: two decades of research on the self-sustained traveling wave of thrombin. Thromb Res. 2015;135(3):423–33. DOI: 10.1016/j. thromres.2014.12.014.
2. Aleksandrov I. V., Belomestnov S. R., Matkovskiy A. A. et al. Antithrombin III level in women with hypertensive disorders during pregnancy. Tromboz, gemostaz i reologiya. 2017;(1):30–3. (In Russ.).
3. Ilyina A.Ya., Mishenko A. L., Martynov A. A. et al. Health status assessment of the newborns with venous thrombosis. Tromboz, gemostaz i reologiya. 2023;(3):19–27. (In Russ.). DOI: 10.25555/ THR.2023.3.1065.
4. Rodgers G. M., Mahajerin A. Antithrombin therapy: current state and future outlook. Clin Appl Thromb Hemost. 2023;29:10760296231205279. DOI: 10.1177/10760296231205279.
5. Nekhaev I. V., Prikhodchenko A. O., Mazurina O. G. et al. Antithrombin III in intensive care. Tromboz, gemostaz i reologiya. 2015;(1):13– 21. (In Russ.).
6. Rybka M. M., Rogalskaya E. A., Meshchanov B. V. et al. Correction of antithrombin deficiency in periopera-tive period in cardiac surgery patients. Tromboz, gemostaz i reologiya. 2020;(3):39–46. (In Russ.). DOI: 10.25555/THR.2020.3.0927.
7. Alami J., Feldman H. A., Hanson A. et al. Efficacy and safety of antithrombin supplementation in neonates and infants on a continuous heparin infusion. Blood. 2023;142(Suppl 1):2639. DOI: 10.1182/ blood-2023-180243.
8. Rojnik T., Sedlar N., Turk N. et al. Comparison of antithrombin activity assays in detection of patients with heparin binding site antithrombin deficiency: systematic review and meta-analysis. Sci Rep. 2023;13(1):16734. DOI: 10.1038/s41598-023-43941-x.
9. Kubiddinov A. F., Saidov Ju.S., Tagozhonov M. Z. et al. Personalized approach to procurement of hemocomponents taking into account hemostasis characteristics of donors. Tromboz, gemostaz i reologiya. 2018;(3):54–9. (In Russ.). DOI: 10.25555/THR.2018.3.0852.
10. Rezaie A. R., Giri H. Anticoagulant and signaling functions ofantithrombin. J Thromb Haemost. 2020;18(12):3142–53. DOI: 10.1111/ jth.15052.
11. Balogh G., Komáromi I., Bereczky Z. The mechanism of high affinity pentasaccharide binding to antithrombin, insights from Gaussian accelerated molecular dynamics simulations. J Biomol Struct Dyn. 2020;38(16):4718–32. DOI: 10.1080/07391102.2019.1688194.
12. Broman L. M. When antithrombin substitution strikes back. Perfusion. 2020;35(1_suppl):34–7. DOI: 10.1177/0267659120906770.
13. Lemondzhava V. N., Chechetkin A. V., Gudkov A. G. et al. Thermolability of factor VIII in donor fresh frozen blood plasma. Gematologiya i transfuziologiya. 2021;66(4):593–609. (In Russ.). DOI: 10. 35754/0234-5730-2021-66-4-593-609.
14. Galstyan G. M., Gaponova T. V., Sherstnev F. S. et al. Clinical guidelines for cryosupernatant transfusions. Gematologiya i transfuziologiya. 2020;65(3):351–9. (In Russ.). DOI: 10.35754/0234-5730-2 020-65-3-351-359.
15. Gerasimenko A. Y., Ichkitidze L. P., Pavlov A. A. et al. Laser system with adaptive thermal stabilization for welding of biological tissues. Biomed Eng. 2016;49:344–8. DOI: 10.1007/s10527-016-9563-9.
16. Lemondzhava V. N., Leushin V. Y., Khalapsina T. M. et al. Automated systems for thawing cryopreserved blood components. Biomed Eng. 2018;51:385–8. DOI: 10.1007/s10527-018-9755-6.
17. Van Cott E. M., Orlando C., Moore G. W. et al.; Subcommittee on Plasma Coagulation Inhibitors. Recommendations for clinical laboratory testing for antithrombin deficiency; Communication from the SSC of the ISTH. J Thromb Haemost. 2020;18(1):17–22. DOI: 10.1111/jth.14648.
18. Piacente C., Martucci G., Miceli V. et al. A narrative review of antithrombin use during veno-venous extracorporeal membrane oxygenation in adults: rationale, current use, effects on anticoagulation, and outcomes. Perfusion. 2020;35(6):452–64. DOI: 10.1177/0267659120913803.
19. Chuprakov D. A., Pozhar K. V. Analysis of methods for calculating optimal parameters for insulin boluses in automated insulin therapy systems with control based on predictive models. Biomed Eng. 2023;57(10):102–6. DOI: 10.1007/s10527-023-10278-8.
20. Gudkov A. G., Leushin V. Y., Sidorov I. A. et al. A functional line of plasma extractors. Biomed Eng. 2021;54(1):350–3. DOI: 10.1007/ s10527-021-10037-7.
21. Gudkov A. G., Leushin V. Y., Sidorov I. A. et al. Devices for sealing polymer containers with blood and its components. Biomed Eng. 2021;54:376–9. DOI: 10.1007/S10527-021-10043-9.
22. Padmore R., Petersen K., Campbell C. et al. Practical application of mathematical calculations and statistical methods for the routine haematology laboratory. Int J Lab Hematol. 2022;44 Suppl 1:11–20. DOI: 10.1111/ijlh.13934.
23. Appert- Flory A., Fischer F., Jambou D., Toulon P. Evaluation and performance characteristics of the automated coagulation analyzer ACL TOP. Thromb Res. 2007;120(5):733–43. DOI: 10.1016/j. thromres.2006.12.002.
24. Ma S., Wang T. The optimal pre-post allocation for randomizedclinical trials. BMC Med Res Methodol. 2023;23(1):72. DOI: 10.1186/ s12874-023-01893-w.
25. Vetrova N. A., Lemondzhava V. N., Filyaev A. A. et al. Prediction of safety indicators for donor blood and its components in a statistically managed technological process based on Bayesian inversion. Biomed Eng. 2022;56:114–8. DOI: 10.1007/s10527-022-10179-2.