Optimal transfusion practices after allogeneic hematopoietic cell transplantation: a systematic scoping review of evidence from randomized controlled trials
Bibliographic record
Abstract
BACKGROUND: Integrating evidence from randomized controlled trials (RCTs) into patient care is needed to optimize patient outcomes. Transfusion support during allogeneic hematopoietic cell transplantation (alloHCT) is a cornerstone of essential supportive care, yet optimal transfusion practices remain unclear. STUDY DESIGN AND METHODS: A scoping review of RCTs in alloHCT was conducted and 14 full-length articles on transfusion practice were identified that reported clinical outcomes after alloHCT. RESULTS: Eight RCTs compared various interventions related to platelet (PLT) transfusion, addressing product storage duration, dosage, and threshold for transfusion. Restrictive prophylactic PLT transfusion strategies were successful at reducing PLT consumption without impacting clinical outcomes. One study, however, reported increased bleeding associated with a strategy whereby patients did not receive prophylactic PLT transfusions. One study of thrombopoietin was associated with reduced PLT transfusion events but no difference in clinical outcomes compared to placebo. Six RCTs examined the utility of recombinant erythropoietin (EPO) in reducing red blood cell (RBC) transfusion dependence. Four trials reported an increase in hemoglobin levels while five studies demonstrated a reduction in RBC utilization; however, clinical outcomes were variably reported and no differences were identified. There were no RCTs examining RBC transfusion strategies, plasma transfusion, or plasma-derived protein administration. CONCLUSION: /L can prevent bleeding and is consistent with recent guidelines. Thrombopoietin and EPO can reduce transfusion requirements; however, potential safety concerns remain and the lack of improvement in clinical outcomes and high cost may limit use. Additional RCTs are needed, particularly with regard to RBC transfusion thresholds, to refine best practices after alloHCT.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.002 |
| 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) | 0.003 | 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 teacher head, 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".