Clinical outcomes in hospitalized plasma and platelet transfusion recipients prior to and following widespread blood donor <scp>SARS‐CoV</scp>‐2 infection and vaccination
Bibliographic record
Abstract
BACKGROUND: The safety of transfusion of SARS-CoV-2 antibodies in high plasma volume blood components to recipients without COVID-19 is not established. We assessed whether transfusion of plasma or platelet products during periods of increasing prevalence of blood donor SARS-CoV-2 infection and vaccination was associated with changes in outcomes in hospitalized patients without COVID-19. METHODS: We conducted a retrospective cohort study of hospitalized adults who received plasma or platelet transfusions at 21 hospitals during pre-COVID-19 (3/1/2018-2/29/2020), COVID-19 pre-vaccine (3/1/2020-2/28/2021), and COVID-19 post-vaccine (3/1/2021-8/31/2022) study periods. We used multivariable logistic regression with generalized estimating equations to adjust for demographics and comorbidities to calculate odds ratios (ORs) and 95% confidence intervals (CIs). RESULTS: Among 21,750 hospitalizations of 18,584 transfusion recipients without COVID-19, there were 697 post-transfusion thrombotic events, and oxygen requirements were increased in 1751 hospitalizations. Intensive care unit length of stay (n = 11,683) was 3 days (interquartile range 1-5), hospital mortality occurred in 3223 (14.8%), and 30-day rehospitalization in 4144 (23.7%). Comparing the pre-COVID, pre-vaccine and post-vaccine study periods, there were no trends in thromboses (OR 0.9 [95% CI 0.8, 1.1]; p = .22) or oxygen requirements (OR 1.0 [95% CI 0.9, 1.1]; p = .41). In parallel, there were no trends across study periods for ICU length of stay (p = .83), adjusted hospital mortality (OR 1.0 [95% CI 0.9-1.0]; p = .36), or 30-day rehospitalization (p = .29). DISCUSSION: Transfusion of plasma and platelet blood components collected during the pre-vaccine and post-vaccine periods of the COVID-19 pandemic was not associated with increased adverse outcomes in transfusion recipients without COVID-19.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".