Guidelines for Cord Blood Unit Selection
Bibliographic record
Abstract
Optimal cord blood (CB) unit selection is critical to maximize the likelihood of successful engraftment and survival after CB transplantation (CBT). However, unit selection can be complex because multiple characteristics must be considered including unit cell dose, donor-recipient human leukocyte antigen (HLA) match, and unit quality. This review provides evidence-based and experience-based comprehensive guidelines for CB unit selection. Topics addressed include the use of both the TNC and the CD34 + cell dose, as well as the CD34 + cell to TNC content ratio to evaluate unit progenitor cell content and engraftment potential, the acceptable TNC and CD34 + cell dose criteria that define an adequate single-unit graft, and the indication and acceptable cell dose criteria for double-unit grafts. The acceptable criteria for 6-loci (HLA-A, -B antigen, -DRB1 allele) and 8-allele (HLA-A, -B, -C, -DRB1) donor-recipient HLA match, the evaluation of patients with donor-specific HLA antibodies, and the multiple determinants of unit quality are also reviewed in detail. Finally, a practical step-by-step guide to CB searches and the principles that guide ultimate graft selection are outlined.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 0.006 |
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".