Specific IgEs passively transferred through a platelet transfusion caused two discrete allergic reactions to food
Bibliographic record
Abstract
Case report A non-atopic 8 year old boy received multiple blood product transfusions as part of his treatment for meduloblastoma. He subsequently experienced anaphylaxis to salmon. Within minutes of eating salmon, he developed angioedema of the lip, facial erythema, throat discomfort and low blood pressure. Before this episode, he regularly ate fish with no reaction. The passive transfer of food specific IgE was suspected and he was advised to carry an epinephrine auto-injector and avoid all vertebrate fish. Specific IgE to salmon by ImmunoCAP was positive. Follow-up was arranged to follow his specific IgE to salmon with the expectation that his allergy would resolve. One week after his anaphylactic episode to fish, he developed an allergic reaction to peanuts. He ate a chocolate peanut butter cup and within 10 minutes he vomited, developed angioedema of the lip and experienced lethargy. Previously, he routinely ate peanuts without any symptoms. Skin prick testing showed positive results to peanut, salmon, mixed fish, and tree nut mix. He had a positive ImmunoCAP to peanut. Approximately 6 months later, he had undetectable ImmunoCAP results to both salmon and peanut. He resumed consumption of salmon and peanuts with no reaction. As part of the adverse event investigation by Canadian Blood Services all donors associated with the reaction were contacted and one donor stated that they have a severe allergy to peanuts, tree nuts, shellfish, and all fish including salmon. This information implicated one specific pooled platelet transfusion in which the platelets were suspended in the plasma of the atopic donor. The donor has been excluded from future donations. Conclusions
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".