Back-to-back comparison of mini-open vs. laparoscopic technique for living kidney donation
Bibliographic record
Abstract
INTRODUCTION: Laparoscopic living donor nephrectomy is the standard of care at high-volume renal transplant centres, with benefits over the open approach well-documented in the literature. Herein, we present a retrospective analysis of our single-institution donor nephrectomy series comparing the mini-open donor nephrectomy (mini-ODN) to the laparoscopic donor nephrectomy (LDN) with regards to operative, donor, and recipient outcomes. METHODS: From 2007-2011, there were 89 cases of mini-ODN, at which point our centre transitioned to LDN; 94 cases were performed from 2011-2014. In total, 366 patients were reviewed, including donor and recipient pairs. Donor and recipient demographics, intraoperative data, postoperative donor recovery, recipient graft outcomes, and financial cost were assessed comparing the surgical approaches. RESULTS: We demonstrate a reduced estimated blood loss (347.83 vs. 90.3 cc), lower intraoperative complication rate (4 vs. 11) and shorter length of hospital stay (2.4 vs. 3.3 days) for patients in the LDN group. Operative time was significantly longer for the LDN group (108.4 vs. 165.9 minutes), although this did not translate to a longer warm ischemia time (mean 2.0 minutes for each group). The rate of delayed graft function and recipient 12-month creatinine were comparable for ODN and LND. Overall cost of LDN was $684 higher for an uncomplicated admission. CONCLUSIONS: Despite a longer surgical time and higher upfront cost, our study supports that LDN yields several advantages over the mini-ODN, with a lower estimated blood loss, fewer intraoperative complications, and shorter length of hospital stay, all while maintaining excellent renal allograft outcomes.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".