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DOI 10.1177/0091270006297229

Медицинская библиотека · Annals of clinical and laboratory science · 2017

Percent cPRA (Calculated Panel Reactive Antibody) Value Predicts Percent of Positive Platelet Crossmatches.

Modi Nishit B, Dresser Mark, Desai Dhaval, Edgar Christopher, Wesnes Keith

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Аннотация

BACKGROUND

Platelet refractoriness or lack of platelet increase after platelet transfusion is seen in patients receiving chronic platelet transfusion support. Antibodies may develop against human platelet antigens (HPA) and/or against HLA class I antigens. Crossmatch (XM) compatible platelets or HLA-identical or HLA-compatible platelets are typically used to manage transfusion refractoriness. We aimed to determine if percent calculated Panel Reactive Antibody (% cPRA) against class I HLA antigens could predict percent positive platelet XM when looking for compatible transfusion products.

METHODS

A retrospective review of all platelet XM performed at our institution between 2008-2012 was performed, and patient characteristics recorded. For each patient, the percentage of all positive platelet XM performed was calculated and compared with the corresponding % cPRA levels against class I HLA antigens.

RESULTS

Mean and median % positive platelet XM for all 50 patients tested in the period 2008-2012 were 61% and 60% (range 0-100%), respectively. Mean and median % cPRA levels were 66% and 68% (range 0-100%), respectively. No correlation was seen between age, sex, race, or diagnosis and positive platelet XM results.

CONCLUSION

The results of our study indicate that the % cPRA correlates well with the % positive platelet XM. Thus, a higher % cPRA alerts the blood bank that additional platelets will be required for XM and/or that it would be beneficial to request HLA-identical or compatible units.

Для цитирования: Modi Nishit B, Dresser Mark, Desai Dhaval, Edgar Christopher, Wesnes Keith. Percent cPRA (Calculated Panel Reactive Antibody) Value Predicts Percent of Positive Platelet Crossmatches.. Annals of clinical and laboratory science. 2017. DOI: 10.1177/0091270006297229.

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