Over 30 Years of Living Liver Donation in North America
Bibliographic record
Abstract
OBJECTIVE: The objective of this study is to determine the incidence of death following living donor hepatectomy. BACKGROUND: Greater than 11,000 living donor hepatectomies have been performed in the United States (US) and Canada over the last 3 decades. Risk of donor death is unknown. METHODS: All living liver donors in the US from 1989 to 2023 were identified within the Organ Procurement Transplantation Network (OPTN) database. Donor death was ascertained. Summary data for number of donors and deaths was collected directly from Canadian centers. US centers with a death within 5 years of donation were surveyed to determine cause of death. RESULTS: In the US, 9400 donor hepatectomies were performed with 79 deaths (0.8%). In Canada 1550 were performed with 4 deaths (0.3%). Median time from donation to death was 8.8 years (0 days-24.5 years). Six deaths occurred perioperatively (<30 days), 2 postoperatively (30-90 days), 17 between 90 days and 5 years, and 53 beyond 5 years. Risk of perioperative/postoperative death decreased over time (0.19%-0.02%) with no deaths since 2016. Causes of perioperative/postoperative death included cardiovascular arrest, liver failure, respiratory arrest, and infection. Causes of death between 90 days and 5 years included trauma, suicide, drug overdose, and cancer. CONCLUSIONS: Perioperative/postoperative death following living donor hepatectomy is rare in North America, with ∼1 death per 5000 donors. Causes of death within 90 days were associated with hepatectomy but deaths beyond 90 days were not attributable to hepatectomy. Defining outcomes after living liver donation is vital for donor selection and counseling.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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 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".