Technical feasibility of robot-assisted laparoscopic radical prostatectomy in renal transplant recipients: Results of a series of 12 consecutive cases
Bibliographic record
Abstract
INTRODUCTION: We evaluate the technical feasibility of robotic prostatectomy in renal transplant recipients. METHODS: We retrospectively analyzed preoperative and perioperative settings, as well as functional and oncologic results of 12 patients operated on between 2009 and 2013. Prostatectomy was performed via a transperitoneal approach without any changing in the ports position. The average age was 61.92 ± 2.98 years. The period between transplant and the diagnosis of adenocarcinoma was 79.7 months. The mean PSA was 7.34 ng/mL (range: 4.9-11). RESULTS: The operative time was 241.3 ± 35.6 minutes with only one conversion and one transfusion. The intervention was difficult due to adhesions on the side of the graft in 50% of cases. There was a case of obstructive acute renal failure resulting from a hematoma of the Retzius treated by percutaneous nephrostomy at D20. There was a majority of pT2c (72.7%), including 3 positive margins (27.3%) and 2 biochemical relapses treated with radiotherapy and hormonotherapy, respectively. The end point prostate-specific antigen was undetectable. There was no significant difference between preoperative and J7 creatinine (p = 0. 22). CONCLUSIONS: Robotic prostatectomy in renal transplant recipients is a safe technique with no serious effects on the allograft.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".