Anonymous Nondirected Living Liver Donation in the United States
Bibliographic record
Abstract
Dear Professor Chapman, We read with great interest this recent article from the University of Virginia group titled “Anonymous Living Liver Donation: Literature Review and Case Series Report.”1 We congratulate the authors for discussing this very important topic and highlighting the experience of 3 centers. As the first and one of the highest volume US centers to perform anonymous living liver donation, we published a review in March 2020 of global experience and perspectives on anonymous nondirected live liver donation (ANLLD).2 This article included data from 105 ANLLDs in the Scientific Registry of Transplant Recipients between 1998 and 2020, along with our own single-center data on long-term health-related quality of life outcomes in 8 of these donors. Although there was a paucity of literature on the topic at the time, we observed excellent outcomes in our patients and concluded that US programs are increasingly willing to consider potential ANLLD. The second publication was a result of collaboration between 3 US centers, University of Colorado, University of Alberta, and University of Southern California contributing a total of 30 ANLLD cases (nearly one-third of those reported in the Scientific Registry of Transplant Recipients at that time).3 Using standardized questionnaires and a survey for live liver donors developed by our center, we concluded that overall, these patients demonstrated acceptable health-related quality of life and were appropriate candidates for partial liver donation. The authors of this recent Transplantation Direct article cited publications from 3 institutions representing 53 ANLLD cases: University of Toronto, Washington University Medical Center, and Hôspital Saint-Luc in Brussels, Belgium.4-8 We are sending this letter to further corroborate that our earlier findings and other recent reports support the conclusions of this article.9,10 Partial liver donation from anonymous donors can be a safe procedure and, given the distinctiveness of this unique patient population, requires careful consideration of institutional policies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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".