A Portrait of Cord Blood Units Distributed for Transplantation from Canadian Blood Services’ Cord Blood Bank: First Analysis
Bibliographic record
Abstract
Background: The Canadian Blood Services Cord Blood Bank (CBS CBB) was created to improve access to stem cell products for transplantation for patients across ethnic groups. An analysis of distributed units is needed to assess the effectiveness of the bank to meet the needs of patients from different ethnic groups. Methods: A descriptive analysis was performed on all cord blood units distributed from the CBS’ CBB as of 30 June 2022. Results: Distribution of the first 60 units based on CBS’ CBB inventory has been linear over time. A similar proportion of cord blood unit (CBU) recipients were pediatric or adult. More than half of the cord blood units (56.7%) were distributed to recipients outside of Canada, and CBUs were used to treat a broad range of hematologic and immune disorders. 43.3% of distributed CBUs were of non-Caucasian ethnicity and 18% were from donors self-reporting as multi-ethnic. The mean total nucleated cell counts and total CD34+ cell counts were 1.9 ± 0.1 × 109 cells and 5.3 ± 0.5 × 106 CD34+ cells, respectively. CD34+ cells per kg (recipient weight) varied significantly between pediatric (age 0–4), adolescent (age 5–17) and adult recipients (age 18 and older) (3.1 ± 0.5, 1.4 ± 0.5 and 0.9 ± 0.07 × 105 CD34+ cells/kg, respectively). HLA matching was 6/6 (15%), 5/6 (47%) or 4/6 (38%). Conclusions: The CBS’ CBB has facilitated the utilization of banked units for patients across a broad range of ages, geographic distribution, ethnicity, and diseases. Distributed units were well matched for HLA alleles and contained robust cell counts, reflecting a high-quality inventory with significant utility.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.013 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".