Using real data for a virtual crossmatch
| Autor: | Jeffrey T. Sholander, Julie A. Houp, Andrea A. Zachary, Mary S. Leffell |
|---|---|
| Rok vydání: | 2009 |
| Předmět: |
Immunosorbent technique
Computer science business.industry Immunology Antibody Affinity Reproducibility of Results Pattern recognition Complement System Proteins General Medicine Cytotoxicity Tests Immunologic Flow Cytometry Sensitivity and Specificity Microspheres Microsphere HLA Antigens Isoantibodies Predictive Value of Tests Histocompatibility Humans Immunology and Allergy Artificial intelligence business Immunosorbent Techniques Monitoring Physiologic |
| Zdroj: | Human Immunology. 70:574-579 |
| ISSN: | 0198-8859 |
| DOI: | 10.1016/j.humimm.2009.06.007 |
| Popis: | Virtual crossmatches have been performed for more than 40 years under the guise of unacceptable antigens. Today, solid-phase assays provide the opportunity for more accurate identification and more precise measurement of the strength of donor-specific antibodies. The process of performing a virtual crossmatch begins with establishing a correlation between the antibody testing assay and the results of actual crossmatches. We provide here data indicating that the identity and strength of DSA defined with solid-phase phenotype panels correlates significantly with the outcome of both cytotoxic (CDC; r = 0.83) and flow cytometric (r = 0.85) crossmatches. Based on the threshold established from these correlations, we were able to correctly predict the results of CDC and flow cytometric crossmatches in 92.8 and 92.4% of cases, respectively. The correlations with single antigen panels were substantially lower (82.6-47.9%) and may be caused by a variety of factors, including variability in the amount and condition of different antigens and extremely high sensitivity, which may make the test less robust. We demonstrate that adding additional information to the solid-phase results can increase the frequency of correct crossmatch prediction. We also present data demonstrating an additional use of the virtual crossmatch in posttransplant monitoring. |
| Databáze: | OpenAIRE |
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