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    On an international scale, guidelines and proposals for lupus anticoagulant detection have been published over the last 20 years, but until now, standardization has not been completely realized. The aim of this study was to evaluate the different ways of interpreting the results of lupus anticoagulant detection for standardization. A retrospective review of 15 447 instances of lupus anticoagulant detection by the diluted Russell Viper Venom test for female patients presenting with problems relating to the areas of reproduction, gynecology and obstetrics was performed. Lupus anticoagulant data were compared between different departments, months, reagent lots and cutoffs. Significant differences were found in patient data between different reagent lots, especially between lots of screening reagents (monthly average: highest 37.96 s vs lowest 33.88 s) and in the positive rates of lupus anticoagulant by different detection cutoffs (47.58% by using LA1/LA2 > 1.20 without normalization as a cutoff in Lot 1 vs 1.52% by using LA1 > 44 s as a cutoff in Lot 3). Compared with the cutoff using the value above the 99th percentile of LA1 for the healthy donors per lot, the cutoff using integrated tests with normalization had the smaller deviation of positive rate between different reagent lots. Pregnant women had higher LA1/LA2 levels than nonpregnant women. Based on the results, normalization is needed because there are significant lot-to-lot variations. Integrated tests with normalization might be a better standard by which to confirm lupus anticoagulant. Pregnant women should have population-specific cutoffs because they have higher LA1/LA2 levels.

    Citation

    Feng Lu, Qingkai Dai, Yuefang Wang, Xia Zhang, Ge Zhang. How to Achieve Standardization? Diluted Russell Viper Venom Test for Lupus Anticoagulant Detection in a Chinese Female Population. Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis. 2021 Jan-Dec;27:10760296211048897

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    PMID: 34657448

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