P‐PB‐1 | Probability of Finding Partially or Fully Compatible Blood for Patients with Sickle Cell Disease: A Descriptive Analysis of Donor‐Recipient Genotype Data
Bibliographic record
Abstract
Alloimmunization substantially increases the risk of future hemolytic transfusion reactions. Alloimmunization can be prevented by transfusing fully matched RBC units, which is made easier by advances in RBC genotyping. This study aimed to estimate the probability of finding a perfect match between the blood of a patient with sickle cell disease (SCD) and the blood of regular donors or donors with rare blood. Moreover, the impact of a simulate intensive recruitment campaign of new donors (+1000) from the general population was performed. Blood donors and patients with SCD were first identified in separate databases. Specifically, the genotype and phenotype data of active donors (N = 194,853—91.0% White, 1.2% Black and 7.8% other; i.e., who donated at least once from January 1, 2019 to December 21, 2021) and rare blood donors (N = 708) were obtained (database compiled and updated by the provincial reference laboratory). Since December 2020, all donors are phenotyped for C, E, c, e, and K antigens (Ag). Data from a cohort of SCD patients previously genotyped (N = 270) were also obtained. The probability of a perfect donor-recipient match was then based on the recorded phenotype (deduced from genotype data) for the ABO, Rh (D, C, E or C/c, E/e), K, Fya, Fyb, V, VS, and hrB Ags. When considering only ABO, D, C, E, and K Ags, the probability of a perfect match was 100.0% with the active and rare donor databases (combined). However, when additionally considering c and e, this probability dropped to 69.3% with the active donor database (alone) and to 78.1% with the active and rare donor databases (combined; Table 1). Finally, when considering all Ags (i.e., adding Fya, Fyb, V, VS, hrB), the probability of a perfect match was only 0.5% with the active donor database (alone) and 23.9% with the active and rare donor databases (combined). Adding 1000 simulated fully typed donors (based on Ag frequencies observed in the active donors) was estimated to increase this probability to a mean of 42.5% (standard deviation = 15.8%). TABLE 1. Observed and simulated match probabilities.
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".