Allergic transfusion reactions from blood components donated by IgA‐deficient donors with and without anti‐IgA: a comparative retrospective study
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: IgA deficiency is common (1/500) and up to 40% of affected individuals will develop anti-IgA. A few studies suggested that passive transfusion of anti-IgA was not associated with an increased risk of allergic reactions. This study was designed to assess the safety of transfusing blood components containing anti-IgA. MATERIALS AND METHODS: IgA-deficient blood donors with and without anti-IgA were identified from Héma-Québec's (HQ) computerized database. IgA deficiency was confirmed by an ELISA method and the presence of anti-IgA by a passive hemagglutination assay. Blood donations from IgA-deficient donors issued to hospitals between March 1999 and December 2004 were retrieved. Medical charts of recipients were reviewed for the occurrence of a suspected transfusion reaction. Presence and nature of transfusion reactions were assessed blindly by an adjudicating committee. RESULTS: A total of 323 IgA-deficient blood products were issued by HQ to 55 hospitals. Of these, 48 agreed to participate [315 blood products (97.5%)]. A total of 272 products were transfused: 174 contained anti-IgA, and 98 did not. Only two minor allergic reactions occurred in each group. Incidence of allergic reactions was 1.15% in the anti-IgA group and 2.04% in the group without anti-IgA (P = 0.91). There was no anaphylactic reaction in either group. CONCLUSIONS: This study indicates that the proportion of allergic reactions does not appear to be greater in recipients of blood components containing anti-IgA compared to recipients of non-anti-IgA-containing components. Allowing donations from IgA-deficient donors with anti-IgA may therefore be contemplated.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".