American Society of Transplant Surgeons: 16th
Bibliographic record
Abstract
Given the large and increasing disparity between supply and demand, allocation decisions of deceased donor kidneys are one of the most sensitive subjects in transplantation today.The revised Kidney Allocation System (KAS) (1) was implemented on December 4, 2104 and was constructed to alter distribution of kidneys to achieve 3 main objectives.The first objective was to improve the offer system efficiency and organ utilization.This objective was addressed by the following: (a) organ quality scoring with the Kidney Donor Profile Index (KDPI) which incorporates multiple donor parameters into a single metric quantifying risk for graft failure along a continuum and captures donor quality better than the historic SCD/ECD dichotomy, (b) use of KDPI categories for allocation priority, (b) regional sharing of KDPI > 85% kidneys, and (c) elimination of paybacks and variances.The second objective was to better approximate graft longevity and recipient longevity.This objective was addressed by priority allocation of the top 20% of survivors (via the newly introduced estimated post-transplant survival [EPTS] scoring for adults based on time on dialysis, candidate age, prior solid organ transplant, and history of diabetes) to get the first chance at the top 20% of kidneys (by KDPI).The third objective is to reduce differences in access for populations described in NOTA such as racial/ethnic minorities, pediatric candidates, and sensitized candidates.This objective is addressed by changing the previous waiting time points to be based on dialysis duration which is intended to effect minorities who have greater barriers to referral and waitlisting; (b) elimination of CPRA of 80% as the cut off to receive points (4 total) and substitution with the CPRA sliding scale which ranges from 0 to 202.10 points, (c) provision of broader sharing to CPRA 99% and 100% sensitized patients regardless of matching, and (d) priority allocation of blood group B recipients, the majority of whom are minorities, to receive A 2 , A 2 B kidneys if deemed eligible by the transplant center.In the first 6 months following KAS implementation several changes were evident in the types of transplants performed (2): an approximately 6-fold increase in transplants for CPRA 99 and 100 candidates; an increase in non-local transplants from 21% to 33%; a drop in the proportion of longevity-mismatched transplants; a significant increase in transplants to African-American recipients from 31.5% prior to KAS to 38.0% of transplants post-KAS, and a higher kidney discard rate in each of the six months post-implementation (average discard rate of 20.3%) compared to the one-year pre-KAS average (18.5%), with the greatest discards being high KDPI kidneys.Lastly, few blood type B registrations have been indicated as clinically eligible and willing to accept an A 2 or A 2 B sub-typed kidney indicating minimal use of this aspect of the system.Many of these changes were expected based on core components of the new systems; however, other changes were unexpected and results are reported monthly (3).ENDNOTES 1. http://optn.transplant.hrsa.gov/media/1200/optn_policies.pdf#nameddest=Policy_08 2. OPTN Kidney Allocation System (KAS) "Out-of-the-Gate Monitoring Report" June 26, 2015 http://optn.transplant.hrsa.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.135 | 0.077 |
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".