Leukocyte Reduction of Red Blood Cell Transfusions Does not Decrease Allosensitization Rates in Potential Kidney Transplant Candidates
Bibliographic record
Abstract
A significant proportion of potential kidney transplant candidates continue to periodically require blood transfusions that carry a risk of allosensitization. Leukocyte reduction (leukoreduction) of blood products has been proved to reduce transfusion-associated allosensitization in patients with hematologic malignancies; however, the effect in potential kidney transplant candidates is unknown. A total of 112 kidney transplant candidates who received red blood cell transfusions while on the transplant waiting list were identified retrospectively. Sixty received a transfusion before leukoreduction (non-LR), and 52 received a transfusion after the local implementation of universal leukoreduction of blood products (LR). There was no difference in transfusion-associated allosensitization rates in patients who received a transfusion during the two eras (non-LR 27% [16 of 60] versus LR 33% [17/52]; NS). Likewise, no difference was observed in subgroups identified as being at high risk of allosensitization (previous pregnancy, transplant, or five or more previous transfusions) or at low risk (no previous allogeneic exposures) (high risk: non-LR 52% versus LR 55%; low risk: non-LR 10% versus LR 8%). Multivariate analysis revealed previous pregnancy to be the only significant risk factor associated with transfusion-associated allosensitization (relative risk, 8.2; 95% confidence interval, 2.4 to 24.0; P = 0.0001). Leukoreduction, in particular, was not associated with any protective effect. In summary, leukoreduction of red blood cell transfusions does not confer any protection against transfusion-associated allosensitization for potential kidney transplant candidates. Physicians who care for patients with ESRD must continue to practice careful transfusion avoidance while alternative strategies to minimize transfusion associated allosensitization are sought.
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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 | 0.005 |
| 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".