Effects of storage on efficacy of red cell transfusion: When is it not safe?
Bibliographic record
Abstract
OBJECTIVE: To review the literature on red blood cell storage and its relationship to the efficacy of transfusion. RESULTS: Well-documented changes occur to the red blood cell product during ex vivo storage. These changes include a reduction in red blood cell deformability, altered red blood cell adhesiveness and aggregability, and a reduction in 2,3-diphosphoglycerate and ATP. Bioactive compounds with proinflammatory effects also accumulate in the storage medium. These changes reduce posttransfusion viability of red blood cells. The clinical effects beyond posttransfusion viability are uncertain, but a growing body of evidence suggests that the storage lesion may reduce tissue oxygen availability, have proinflammatory and immunomodulatory effects, and influence morbidity and mortality. There are no published randomized, control trials examining the effect of storage duration on morbidity and mortality. Leukoreduction improves the quality of stored red blood cell products and in some studies has been shown to reduce morbidity and mortality. CONCLUSION: Although storage duration influences the quality of red blood cell product, there is currently insufficient evidence to advocate shorter storage periods for red blood cell products.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".