Blood donor <scp>SARS</scp>‐<scp>CoV</scp>‐2 infection or vaccination and adverse outcomes in plasma and platelet transfusion recipients
Bibliographic record
Abstract
BACKGROUND: Despite data supporting the safety of SARS-CoV-2 vaccination, concerns regarding the receipt of blood products from donors previously infected or vaccinated against SARS-CoV-2 persist. We assessed whether transfusions of plasma or platelet products from donors with prior SARS-CoV-2 infection or vaccination were associated with adverse outcomes in patients without COVID-19. METHODS: We linked donor SARS-CoV-2 spike and nucleocapsid antibody data and vaccination history to blood products transfused between June 1, 2020 and March 31, 2022. We used logistic regression, adjusting for demographics and comorbidities, to calculate odds ratios and 95% confidence intervals (CI) for posttransfusion thrombosis, increased respiratory requirement, and hospital mortality. Outcomes were assessed as per transfused unit from previously infected or vaccinated donors compared to units from uninfected or unvaccinated donors. RESULTS: Among 8715 hospitalizations of 7773 transfusion recipients linked to donor SARS-CoV-2 antibody data, there were 251 thromboses, 700 hospitalizations with increased respiratory requirements, and 1443 deaths. Among 15,167 transfused plasma units, 4993 and 1106 were from vaccinated donors and previously infected donors, respectively. Among 19,295 transfused platelet units, 8530 and 1368 were from vaccinated and previously infected donors, respectively. There were no associations between the transfusion of blood products from vaccinated or previously infected donors and thrombosis, increased respiratory requirements, or hospital mortality (all CI including 1). Nor were there associations between the receipt of blood products from recently infected or vaccinated donors or high SARS-CoV-2 antibody titers and adverse outcomes. DISCUSSION: Donor SARS-Cov-2 infection and vaccination were not associated with adverse patient outcomes and do not need to be considered in blood allocation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".