An international investigation into AB plasma administration in hospitals: how many AB plasma units were infused? The HABSWIN study
Bibliographic record
Abstract
BACKGROUND: Typical practice is to transfuse group-specific plasma units; however, there are situations where group AB plasma (universal donor) is issued to group A, B, or O recipients. If demand for group AB plasma exceeds collections, there is potential for shortage. This project explored the patterns of group AB plasma utilization at hospitals around the world. STUDY DESIGN AND METHODS: The study had two phases: a survey that inquired about hospital group AB plasma inventory, policies, and transfusion practices and a retrospective review of 2014 calendar year data where participants submitted information on plasma disposition including ABO group of unit and recipient, transfusion location, and select indications. Recruitment occurred through snowball sampling. Descriptive analyses were performed. RESULTS: Survey data were received from 25 centers across 10 countries; of those, 15 participants contributed to the data collection component. These 15 centers transfused a total of 43,369 AB plasma units during the study period. Only 1496 of 5541 (27%) group AB plasma units were transfused to group AB recipients. Transfusion policies, practices, and patterns were variable across sites. CONCLUSION: Group AB plasma units are frequently transfused to non-AB recipients. Whether transfusing 73% of group AB plasma units to non-AB recipients is the ideal inventory management strategy remains to be determined.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".