Two cases of platelet transfusion refractoriness associated with anti‐CD36
Bibliographic record
Abstract
BACKGROUND: Antibodies to platelet (PLT) glycoprotein (GP) IV (CD36) have been implicated in rare cases of PLT refractoriness, particularly in non-Caucasians. We report two cases of PLT transfusion refractoriness linked to anti-CD36. STUDY DESIGN AND METHODS: A 5-year-old female of Lebanese descent and a 70-year-old male of Chinese descent both failed to respond to HLA-matched PLT transfusions during acute myelogenous leukemia induction therapy. Antibody screening was performed using a PLT antibody solid-phase kit (PAKPLUS, GTI Diagnostics), followed by the monoclonal antibody-specific immobilization of PLT antigen (MAIPA) test and, for the second case, the modified antigen capture enzyme-linked immunosorbent assay (MACE). RESULTS: Both patients demonstrated antibody to GP IV (CD36) on the PAKPLUS assay. On MAIPA testing, both phenotyped as CD36 negative. Anti-CD36 was demonstrated by MAIPA in the first case. In the second case, antibodies were not detected by MAIPA and variably detectable by MACE, depending on the mouse monoclonal antibody (MoAb) used. Because no Canadian CD36-negative donors were available, antigen-negative plateletpheresis units from the BloodCenter of Wisconsin were successfully transfused. CONCLUSION: Two cases of clinically significant CD36 antibodies are reported. Investigation of one case was complicated by steric inhibition of binding in the MAIPA and MACE assays with certain MoAbs. The cases demonstrate the importance of maintaining an ethnically diverse pool of rare donors and the value of international cooperation in the management of these patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".