Evaluating RhD assessment by automated methodology: A potential "blind spot" for RhD variant identification

Area of Science:

• Blood group antigen research
• Transfusion medicine
• Immunogenetics

Background:

• The Rh blood group system is highly polymorphic, with RHD variant alleles potentially causing anti-D antibody formation.
• Automated testing platforms can miss certain D variants, posing risks for specific patient populations.
• Transfusion services need accurate methods to identify D variants in at-risk individuals.

Purpose of the Study:

• To implement and evaluate a blood bank protocol for identifying patients requiring RHD genotyping.
• To assess the effectiveness of the protocol in detecting D variants missed by automated testing.
• To compare the performance of automated platforms versus traditional tube testing for D variant detection.

Main Methods:

• A protocol was implemented at Yale New Haven Hospital to identify patients for RHD genotyping.
• Patient RHD genotyping was performed from December 2020 to January 2024.
• Serological reactivities were compared between automated platforms (gel and solid phase) and traditional tube testing.

Main Results:

• Of 74 genotyped patients, 53 (71.6%) exhibited D variants, with 29 having types associated with anti-D formation.
• Traditional tube testing showed significantly lower reactivity than the gel column platform (p=0.0001).
• Solid-phase testing showed no significant difference compared to tube testing (p=0.15).

Conclusions:

• Automated gel platforms have a "blind spot" that can lead to misclassification of D variants.
• The established protocol effectively identifies high-risk patients needing RHD genotyping via routine tube testing.
• This approach enhances patient safety by minimizing missed cases of clinically significant D variants in transfusion practices.