Estimated Association Between Organ Availability and Presumed Consent in Solid Organ Transplant
Bibliographic record
Abstract
Importance: Presumed consent, or an opt-out organ transplant policy, has been adopted by many countries worldwide to increase organ donation. The implication of such a policy for transplants in the United States is uncertain, however. Objective: To simulate the potential implications of a presumed consent policy in the United States. Design, Setting, and Participants: In a decision analytical model, a simulation model was developed using cohort data from January 1, 2004, to December 31, 2014, in the Organ Procurement and Transplantation Network Standard Transplant Analysis and Research files. All US patients (n = 524 359) who were on the waiting list for at least 1 solid organ and all deceased organ donors during the study period were included in the analyses. All data and statistical analyses were performed from January 30, 2019, to July 31, 2019. Main Outcomes and Measures: Increase in the organs available for donation and life-years gained associated with a 5%, 15%, or 25% increase in deceased donors, based on the published changes from a presumed consent policy. Results: This study considered 524 359 unique candidates (aged ≥18 years; 320 908 [61.2%] male) for a solid organ transplant from January 1, 2004, to December 31, 2014. With a base case scenario of a 5% presumed consent-associated increase in donors, the removals (owing to death or illness) from the waiting list for all organs would have an associated 3.2% to 10.4% mean reduction, depending on the random or ideal allocation of new organs to patients on the waiting list. Sensitivity analyses showed that waiting list removals could be decreased up to 52%; however, this reduction was not enough to completely eliminate waiting list removals during the study period. The biggest estimated increases in annual life-years gained associated with a presumed consent policy were in kidney transplant candidates (95% CIs by deceased donor increase: 5% increase, 3440-3466 years; 15% increase, 10 321-10 399 years; 25% increase, 17 201-17 332 years) and liver transplant candidates (95% CIs by deceased donor increase: 5% increase, 898-905 years; 15% increase, 2693-2714 years; 25% increase, 4448-4523 years). Adoption of a presumed consent policy could result in a 4295-year (95% CI, 4277-4313 years) to 11 387-year (95% CI, 11 339-11 435 years) increase in life-years, accounting for the survival advantages associated with a transplant. Conclusions and Relevance: In this study, presumed consent was estimated to be associated with modest but important improvement in the number of organ transplants and increases in life-years gained for patients awaiting an organ transplant. Further consideration and even debate about the ethical and public policy implications of a presumed consent policy are warranted.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".