The Effect of Sex-Mismatched Red Blood Cell Transfusion on Endothelial Cell Activation in Critically Ill Patients
Bibliographic record
Abstract
Background: Observational studies suggest that sex-mismatched transfusion is associated with increased mortality. Mechanisms driving mortality are not known but may include endothelial activation. The aim of this study is to investigate the effects of sex-mismatched red blood cell (RBC) transfusions on endothelial cell activation markers in critically ill patients. Study Design and Methods: In patients admitted to the intensive care unit who received a single RBC unit, blood samples were drawn before (T0), 1 h after (T1), and 24 h after transfusion (T24) for analysis of soluble syndecan-1, soluble intercellular adhesion molecule-1, soluble thrombomodulin (sTM), von Willebrand factor antigen, interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNFα). Changes in the levels of these factors were compared between sex-matched and sex-mismatched groups. Results: Of 69 included patients, 32 patients were in the sex-matched and 37 patients were in the sex-mismatched group. Compared to baseline, sex-matched transfusion was associated with significant reduction in sTM level (p value = 0.03). Between-group comparison showed that levels of syndecan-1 and sTM were significantly higher in the sex-mismatched group compared to the sex-matched group at T24 (p value = 0.04 and 0.01, respectively). Also, TNFα and IL-6 levels showed a statistically marginal significant increase compared to baseline in the sex-mismatched group at T24 (p value = 0.06 and 0.05, respectively), but not in the sex-matched group. Discussion: Transfusion of a single sex-mismatched RBC unit was associated with higher syndecan-1 and sTM levels compared to transfusion of sex-matched RBC unit. These findings may suggest that sex-mismatched RBC transfusion is associated with endothelial activation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".