Restricting Kidney Transplant Wait‐Listing for Obese Patients: Let's Stop Defending the Indefensible
Bibliographic record
Abstract
The allocation of limited medical resources represents an ethical dilemma that continues to generate lively debates. While the allocation of allografts to wait-listed patients is done in a transparent manner, with its rules open to public debate and prone to continuous improvement, the practice of wait-listing is not centrally regulated, and its rules are often less scrutinized. Denial of kidney transplant wait-listing to obese individuals has been a common practice by most transplant centers. On the face of it, this practice is justified by commonly accepted ethical standards, yet there is now mounting evidence that these justifications do not withstand closer scrutiny. A candid and open debate in the Nephrology and Transplant community is needed to examine the true motivations that underlie the practice of denying wait-listing to obese individuals, and to find a solution that is truly in the best interest of our patients.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".