Abstracts / Human Immunology 78 (2017) 51–254
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EDTA FULLY OVERCOMES THE PROZONE EFFECT IN LUMINEX-BASED HLA ANTIBODY ASSAYS REGARDLESS OF TECHNICAL MODIFICATIONS John J. Xin, Nicholas K. Brown, Rebecca L. Upchurch, Jerome G. Weidner, Susana R. Marino. University of Chicago Medicine, Chicago, IL, United States. Aim: Our laboratory has recently reported that serum treatment with EDTA is sufficient to overcome the prozone effect. However, it has been reported that in rare cases, specimens are partially resistant to EDTA treatment, and serum dilutions are still necessary. Although we have not encountered such case in our laboratory, we sought to determine if differences in the technical aspects of the assay may contribute to EDTA’s effectiveness. Methods: We screened samples sent to our laboratory for HLA antibody testing for suspected prozone effect, based on MFI values of >15,000. Selected samples were tested in three protocols. Protocol #1: to determine the presence of prozone effect, serum samples were frozen, thawed, centrifuged (14,000 rpm for 10 min), and tested at neat, 1:4, 1:16, 1:64, and 1:264 by single antigen (SA) bead assays (One Lambda). Protocol #2: to test the clinically-validated method used by our lab, samples were frozen, thawed, centrifuged, treated with EDTA (4 mM), and tested at neat only; incubation and washing was performed in a 1 lM filter plate on a vacuum plate-washing system (Biotek ELx50). Protocol #3: to test the effect of EDTA in fresh samples with the manual washing method, fresh serum samples were centrifuged, treated with EDTA, and then tested at neat only; incubation and washing was performed in a traditional round-bottom plate. Data were acquired on a Luminex-200 and analyzed with HLAFusion software (One Lambda). Results: We identified prozone effects in 18 patients’ samples: 8 patients’ class I antibodies, 8 patients’ class II antibodies, and 2 patients’ class I and II antibodies. Following EDTA treatment, fresh and frozen samples showed similar MFI values for the corresponding assignments, including 138 class I and 103 class II specificities. In addition, all determined specificities showed higher MFI values in EDTA-treated samples than the peak MFI value in sample with dilution only, regardless of which technical protocol was used. Conclusions: Samples with prozone effect resistant to EDTA treatment were not detected in our study, independent of technical variability for sample processing. EDTA treatment fully overcomes prozone effect in our testing system. Factors causing low efficacy of EDTA in rare cases remain unknown.
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CREATION OF A PLATELET TRANSFUSION REFRACTORINESS WEB APP FOR USE AT THE POINT-OF-CARE William J. Gordon a,b,c, Jane Baronas d, William J. Lane d,c. aClinical Informatics and Innovation, Brigham and Women’s Hospital, Boston, MA, United States; bDepartment of Medicine, Massachusetts General Hospital, Boston, MA, United States; cHarvard Medical School, Boston, MA, United States; dDepartment of Pathology, Brigham and Women’s Hospital, Boston, MA, United States. Aim: Platelet transfusions are a cornerstone of therapy for patients who develop thrombocytopenia while undergoing hematopoietic stem cell transplantation (HSCT). Many of these patients demonstrate anti-HLA alloantibody mediated platelet transfusion refractoriness (PTR) and require HLA-matched platelets. The calculated panel reactive antibody (cPRA) is a useful tool for identifying patients at risk for PTR, but it requires manual intervention to calculate and so it is only calculated when requested. However, routine use of cPRA before every HSCT, using the existing pre-HSCT alloantibody results, could identify PTR earlier and more efficiently manage its complex transfusion needs for improved patient care. To accomplish this goal, we created an electronic medical record (EMR) web app for use by clinicians, blood bank/donor center, and tissue typing lab to better identify and manage PTR patients. Methods: An online cPRA web-service was created to electronically receive alloantibody data and return cPRA values for several different ethnicities. Additionally, to increase flexibility, the cPRA web-service calculation can be customized with user defined antigen frequencies and epitopes. To utilize the cPRA web-service, a PTR web app was created with connections to several clinical data sources including: Tissue Typing Lab, Blood Bank, Donor Center, and EMR. The PTR web app was embedded into the EMR so that it could be easily viewed while caring for patients undergoing HSCT. Platelet utilization and transfusion effectiveness were compared before and after implementation. Results: The cPRA web-service allows for automated computer generated cPRAs, making it feasible to calculate up-to-date cPRAs for every HSCT patient. The web app displays platelet counts along with platelet transfusion events, platelet units in inventory, and has a section for the clinical care teams and lab staff to communicate. We plan on making the cPRA web-service publicly available for others to use and customize. Conclusions: We built a customizable cPRA web-service and platelet transfusion visualization web app to provide better point-of-care access to real time cPRA values to enable PTR risk stratification of HSCT patients. The web app also summarizes all of the key clinical data to efficiently manage PRT and improve platelet usage.
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