Transfusion of Uncrossmatched Group O Erythrocyte-containing Products Does Not Interfere with Most ABO Typings
Bibliographic record
Abstract
BACKGROUND: Group O erythrocytes and/or whole blood are used for urgent transfusions in patients of unknown blood type. This study investigated the impact of transfusing increasing numbers of uncrossmatched type O products on the recipient's first in-hospital ABO type. METHODS: This was a retrospective cohort study. Results of the first ABO type obtained in adult, non-type O recipients (i.e., types A, B, AB) after receiving at least one unit of uncrossmatched type O erythrocyte-containing product(s) for any bleeding etiology were analyzed along with the number of uncrossmatched type O erythrocyte-containing products administered in the prehospital and/or in hospital setting before the first type and screen sample was drawn. RESULTS: There were 10 institutions that contributed a total of 695 patient records. Among patients who received up to 10 uncrossmatched type O erythrocyte-containing products, the median A antigen agglutination strength in A and AB individuals on forward typing (i.e., testing the recipient's erythrocytes for A and/or B antigens) was the maximum (4+), whereas the median B antigen agglutination strength among B and AB recipients of up to 10 units was 3 to 4+. The median agglutination strength on the reverse type (i.e., testing the recipient's plasma for corresponding anti-A and -B antibodies) was very strong, between 3 and 4+, for recipients of up to 10 units of uncrossmatched erythrocyte-containing products. Overall, the ABO type of 665 of 695 (95.7%; 95% CI, 93.9 to 97.0%) of these patients could be accurately determined on the first type and screen sample obtained after transfusion of uncrossmatched type O erythrocyte-containing products. CONCLUSIONS: The transfusion of smaller quantities of uncrossmatched type O erythrocyte-containing products, in particular up to 10 units, does not usually interfere with determining the recipient's ABO type. The early collection of a type and screen sample is important.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".