ABO-adjusted calculated panel reactive antibody (cPRA): A unified metric for immunologic compatibility in kidney transplantation
Bibliographic record
Abstract
Implementation of the kidney allocation system in 2014 greatly reduced access disparity due to human leukocyte antigen (HLA) sensitization. To address persistent disparity related to candidate ABO blood groups, herein we propose a novel metric termed "ABO-adjusted cPRA," which simultaneously considers the impact of candidate HLA and ABO sensitization on the same scale. An ethnic-weighted ABO-adjusted cPRA value was computed for 190 467 candidates on the kidney waitlist by combining candidate's conventional HLA cPRA with the remaining fraction of HLA-compatible donors that are ABO-incompatible. Consideration of ABO sensitization resulted in higher ABO-adjusted cPRA relative to conventional cPRA by HLA alone, except for AB candidates since they are not ABO-sensitized. Within cPRA Point Group = 99%, 43% of the candidates moved up to ABO-adjusted cPRA Point Group = 100%, though this proportion varied substantially by candidate blood group. Nearly all O and most B candidates would have elevated ABO-adjusted cPRA values above this policy threshold for allocation priority, but relatively few A candidates displayed this shift. Overall, ABO-adjusted cPRA more accurately measures the proportion of immune-compatible donors compared with conventional HLA cPRA, especially for highly sensitized candidates. Implementation of this novel metric could enable the development of allocation policies permitting more ABO-compatible transplants without compromising equity.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".