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Record W2331670110 · doi:10.1016/j.juro.2016.02.1816

V4-12 ROBOTIC SUPRAPUBIC PROSTATECTOMY- A NOVEL TECHNIQUE

2016· article· en· W2331670110 on OpenAlexaboutno aff
Mona Yezdani, Abdo Kabarriti, Sylvia Yu, Alice McGill, Kelly Monahan, David I. Lee

Bibliographic record

VenueThe Journal of Urology · 2016
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineFoley catheterProstatectomyFoleyNeck of urinary bladderFasciaDissection (medical)SurgeryProstateGeneral surgeryCatheterUrinary bladderCancer

Abstract

fetched live from OpenAlex

You have accessJournal of UrologyRobotics – Prostate/Novel Imaging1 Apr 2016V4-12 ROBOTIC SUPRAPUBIC PROSTATECTOMY- A NOVEL TECHNIQUE Mona Yezdani, Abdo Kabarriti, Sylvia Yu, Alice McGill, Kelly Monahan, and David Lee Mona YezdaniMona Yezdani More articles by this author , Abdo KabarritiAbdo Kabarriti More articles by this author , Sylvia YuSylvia Yu More articles by this author , Alice McGillAlice McGill More articles by this author , Kelly MonahanKelly Monahan More articles by this author , and David LeeDavid Lee More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2016.02.1816AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES The treatment of benign prostatic hypertrophy has evolved in many ways through technologic advances. Treatment options include endoscopic, open, laparoscopic, and robotic interventions. Simple robotic prostatectomy has been described using many different techniques including retrovesical, transvesical, and extraperitoneal approaches. In this video, we demonstrate a novel robotic approach to the simple suprapubic prostatectomy. The demonstrated technique is recognizable and easily adaptable for those skilled in radical robotic prostatectomy. METHODS The start of this surgery is similar to radical approach with incision of the umbilical ligaments, dropping of the bladder, and incision of endopelvic fascia. The superficial venous complex is sutured. The bladder neck is dissected as we normally do for a robotic prostatectomy. The bladder neck is dissected until the Foley catheter is identified. The foley catheter is pulled anteriorly and used as a retractor. The prostatic adenoma can now be seen. The posterior bladder neck is now dissected. Verumontanum is identified. Dissection of the adenoma is begun posteriorly. Anteriorly, the lateral planes are established and this plane is continued all the way around to the very near to the apex of the prostate bilaterally. The anterior prostate is then divided in half to expose the anterior of the prostatic urethra. The adenoma is then removed. The distal apical urethral tissue was identified. The verumontanum is inspected and confirmed to be intact. #3-0 Quill suture is used to re-approximate the bladder neck to the urethra in a running fashion starting at the 5 o'clock position up until 12 o'clock position. An 18-French Foley catheter is placed and the remaining lateral bladder incision is closed with a running #3-0 V-lock. RESULTS This method has multiple advantages. It allows familiarity for those who have performed a radical robotic prostatectomy. In comparison with the open approach, it provides improved visualization. Our approach provides improved hemostasis. An 18 Fr catheter is placed at the end of the case. A suprapubic tube and continuous bladder irrigation are not necessary. This approach allows for quick recovery. Our patients are typically discharged on POD #1 with an indwelling Foley catheter. Given our watertight urethral approximation, the risk of urine leakage is very low. CONCLUSIONS In conclusion, our novel technique for robotic suprapubic simple prostatectomy is easily adaptable for those who are familiar with a robotic radical prostatectomy. The next steps of this study will be to assess for functional outcome after the procedure. © 2016FiguresReferencesRelatedDetails Volume 195Issue 4SApril 2016Page: e520 Advertisement Copyright & Permissions© 2016MetricsAuthor Information Mona Yezdani More articles by this author Abdo Kabarriti More articles by this author Sylvia Yu More articles by this author Alice McGill More articles by this author Kelly Monahan More articles by this author David Lee More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.005

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.

Opus teacher head0.020
GPT teacher head0.272
Teacher spread0.252 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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