[Urachal adenocarcinoma treated with robotic assisted laparoscopy partial cystectomy].
Bibliographic record
Abstract
OBJECTIVE: To describe a case of urachal adenocarcinoma treated with robotic assisted laparoscopic partial cystectomy and en-bloc exeresis of urachus and umbilicus and bibliographic review. METHODS: A 63 year-old man with hematuria and hypogastric pain. He was diagnosed of urachal adenocarcinoma by transurethral resection and axial tomography. We performed a robotic assisted laparoscopic partial cystectomy using a da Vinci® S HD (Intuitive Surgical System) device. We describe the surgical technique and examine total length of time for surgery and for console, pathology report, margin status, postoperative outcome and oncological status 7 months after surgery. RESULTS: 4 ports were used for robotic arms and one additional for the assistant. Cystoscopy was performed during surgery to mark tumor margins. Bladder was closed using a running suture with Poliglactin 0. Total length time for surgery was 2hs 28 minutes, console time was 1h54'. Two days later patient was discharged and no complication was reported. After two weeks Foley cathether was removed and bladder volume was 300ml. Pathology report informed undifferentiated urachal adenocarcinoma with perivesical tissue infiltration with margins free from tumor, corresponding to Sheldon IIIB and Ontario III classification. Seven months later patient was fee from recurrence. CONCLUSION: Robotic assisted laparoscopy partial cystectomy with en-bloc exeresis of urachal and umbilicus is feasible.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".