Does the Canadian allocation system for highly sensitized patients work?
Bibliographic record
Abstract
PURPOSE OF REVIEW: The number of sensitized heart transplant candidates is rising. Highly sensitized patients are disadvantaged because they encounter longer waiting times to heart transplant. Strategies to reduce their waiting times include waitlist prioritization and desensitization therapies. The purpose of this review is to describe the listing category for highly sensitized patients in the Canadian allocation system, examine the advantages and limitations of this strategy and provide an approach to the management of the highly sensitized patient awaiting heart transplant. RECENT FINDINGS: Analysis of data from the United Network of Organ Sharing shows that the incidence of death or removal from the waitlist in patients listed for heart transplant increases as the calculated panel reactive antibody (cPRA) increases and is independent of medical urgency. In the Canadian allocation system, patients with cPRA more than 80% have a similar incidence of death on the waitlist as less sensitized patients, suggesting they survive to be transplanted. Furthermore, prioritizing and transplanting highly sensitized patients has been associated with acceptable post-transplant outcomes. SUMMARY: The Canadian allocation system prioritizes highly sensitized patients to increase equity and access to transplantation while maintaining good post-transplant outcomes. Not all highly sensitized patients can wait for an organ, even if prioritized. A pragmatic individualized approach would consider the medical stability of the patient, the likelihood of transplant with a negative crossmatch and then determine whether waitlist prioritization or desensitization is the more appropriate strategy.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".