Storage time of transfused red blood cells and impact on clinical outcomes in hematopoietic stem cell transplantation
Bibliographic record
Abstract
BACKGROUND: Red blood cell (RBC) transfusion may prolong recovery in some patients, perhaps due to changes that occur during more prolonged RBC storage. We examined the impact of RBC transfusion and the age of transfused RBC units on clinical outcomes in hematopoietic stem cell transplantation (HSCT). STUDY DESIGN AND METHODS: Data concerning RBC transfusions between Day 0 and Day +30 were analyzed for patients undergoing HSCT (n = 555) at a single institution. "Old" RBC units were defined as those stored for 15 days or longer. RESULTS: The proportion of old RBC units transfused and the mean age of transfused units did not correlate with 100-day nonrelapse mortality, organ-specific toxicity, length of stay (LOS), or incidence of intensive care unit (ICU) admission (p > 0.05). In comparing the 71 patients who received only old RBC units with 218 patients who received only "new" RBC units, there was no increase in adverse clinical outcomes after HSCT. Autologous transplant recipients (n = 355, 3.8 units/patient) were more likely to avoid RBC transfusion and received fewer units compared with allogeneic recipients (n = 200, 6.4 units/patient, p < 0.0001). The mean number of transfused RBC units was greater in patients admitted to the ICU (10.5 units vs. 3.7 units/patient, p < 0.01), correlated with longer LOS (p < 0.0001), and correlated with increasing number of organ systems with toxicity of at least Grade 2 (p < 0.0001). CONCLUSION: The importance of RBC storage time does not appear to influence clinical outcomes in HSCT. Patients with increased RBC transfusion requirements have greater toxicity after HSCT. Whether RBC transfusion contributes to toxicity, however, remains unclear.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".