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Evaluating RhD assessment by automated methodology: A potential "blind spot" for RhD variant identification
Nalan Yurtsever1, Christopher A Tormey1, Laurie Bizzario1
1Department of Laboratory Medicine, Yale University School of Medicine, New Haven, Connecticut, USA.
Background:
The Rh blood group is highly polymorphic, and individuals with RHD variant alleles can form antibodies against antigens found in the conventional RhD protein. To prevent transfusion of D+ blood to groups at risk of forming anti-D antibodies, such as women of childbearing age and newborns, our transfusion service has established protocols to accurately identify D variants that can be missed by automated testing platforms in these important patient populations.
Study Design And Methods:
We implemented a blood bank protocol at Yale New Haven Hospital to identify patients to perform RHD genotyping on and evaluated the effectiveness of the protocol to detect D variants in patients undergoing ABO/D typing from December 2020 to January 2024. We compared serological reactivities between automated platforms (Grifols gel column and Werfen solid phase) and traditional tube testing on patients with confirmed RHD genotyping.
Results:
Among 74 patients genotyped, 53 exhibited D variants, yielding a positive predictive value (PPV) of 71.6%. A total of 29 patients had variant D types associated with anti-D formation. Tube testing showed significantly lower reactivity compared to the gel platform (p = .0001). Solid-phase testing did not demonstrate significant differences from tube testing (p = .15).
Discussion:
Our findings reveal a critical "blind spot" in automated gel platforms, which may lead to misclassification of D variants. Our established protocol effectively identifies high-risk patients who need RHD genotyping by using routine tube testing. This approach aims to minimize missed cases of clinically significant D variants, ultimately improving patient safety in transfusion practices.
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