Intraoperative ‘No Go’ Donor Hepatectomies in Living Donor Liver Transplantation
Bibliographic record
Abstract
Donor safety is the paramount concern of living donor liver transplantation (LDLT). Although LDLT is employed worldwide, there is little data on rates and causes of 'no go' hepatectomies-patients brought to the operating room for possible donor hepatectomy whose procedure was aborted. We performed a single-center, retrospective review of all patients brought to the operating room for donor hepatectomy between October 2000 and November 2008. Of 257 right lobe donors, the donor operation was aborted in 12 cases (4.7%). The main reasons for stopping the operation were aberrant ductal or vascular anatomy (seven cases), unsuitable liver quality (three cases) or unexpected intraoperative events (two cases). Over the median period of follow-up of 23 months, there were no long-term complications of patients with aborted donor procedures. This report focuses exclusively on an important issue: the frequency and causes of no go decisions at a single large volume North American LDLT center. The rate of no go donor hepatectomies should be as low as possible without compromising donor safety--however, even with rigorous preoperative evaluation the rate of donor abortions will be significant. The default surgical position should always be to abort the donor operation if there is an unexpected finding that places the donor at increased risk.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".