Donor-recipient sex is associated with transfusion-related outcomes in critically ill patients
Bibliographic record
Abstract
Transfusion of red blood cells (RBCs) from female donors has been associated with increased risk of mortality. This study aims to investigate the associations between donor-recipient sex and posttransfusion mortality and morbidity in critically ill patients who received RBC transfusions from either male-only donors or from female-only donors (unisex-transfusion cases). Survival analysis was used to compare 4 groups: female-to-female, female-to-male, male-to-female, and male-to-male transfusion. Multivariate logistic model was used to evaluate the association between donor sex and intensive care unit (ICU) mortality. Associations between transfusion and acute kidney injury (AKI), acute respiratory distress syndrome (ARDS), and nosocomial infections were assessed. Of the 6992 patients included in the original cohort study, 403 patients received unisex-transfusion. Survival analysis and the logistic model showed that transfusion of female RBCs to male patients was associated with an increased ICU mortality compared with transfusion of female RBCs to female patients (odds ratio, 2.43; 95% confidence interval, 1.02-5.77; P < .05). There was a trend toward increased ARDS in patients receiving RBC from female donors compared with those receiving blood from males (P = .06), whereas AKI was higher in donor-recipient sex-matched transfusion groups compared with sex-mismatched groups (P = .05). This was an exploratory study with potential uncontrolled confounders that limits broad generalization of the findings. Results warrant further studies investigating biological mechanisms underlying the association between donor sex with adverse outcomes as well as studies on the benefit of matching of blood between donor and recipient.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".