Bimanual examination of the retrieved specimen and regional hypothermia during robot-assisted radical prostatectomy: a novel technique for reducing positive surgical margin and achieving pelvic cooling

2014 ◽  
Vol 114 (6) ◽  
pp. 955-957 ◽  
Author(s):  
Wooju Jeong ◽  
Akshay Sood ◽  
Khurshid R. Ghani ◽  
Dan Pucheril ◽  
Jesse D. Sammon ◽  
...  
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ching-Wei Yang ◽  
Hsiao-Hsien Wang ◽  
Mohamed Fayez Hassouna ◽  
Manish Chand ◽  
William J. S. Huang ◽  
...  

AbstractThe positive surgical margin (PSM) and biochemical recurrence (BCR) are two main factors associated with poor oncotherapeutic outcomes after prostatectomy. This is an Asian population study based on a single-surgeon experience to deeply investigate the predictors for PSM and BCR. We retrospectively included 419 robot-assisted radical prostatectomy cases. The number of PSM cases was 126 (30.1%), stratified as 22 (12.2%) in stage T2 and 103 (43.6%) in stage T3. Preoperative prostate-specific antigen (PSA) > 10 ng/mL (p = 0.047; odds ratio [OR] 1.712), intraoperative blood loss > 200 mL (p = 0.006; OR 4.01), and postoperative pT3 stage (p < 0.001; OR 6.901) were three independent predictors for PSM while PSA > 10 ng/mL (p < 0.015; hazard ratio [HR] 1.8), pT3 stage (p = 0.012; HR 2.264), International Society of Urological Pathology (ISUP) grade > 3 (p = 0.02; HR 1.964), and PSM (p = 0.027; HR 1.725) were four significant predictors for BCR in multivariable analysis. PSMs occurred mostly in the posterolateral regions (73.8%) which were associated with nerve-sparing procedures (p = 0.012) while apical PSMs were correlated intraoperative bleeding (p < 0.001). A high ratio of pT3 stage after RARP in our Asian population-based might surpass the influence of PSM on BCR. PSM was less significant than PSA and ISUP grade for predicting PSA recurrence in pT3 disease. Among PSM cases, unifocal and multifocal positive margins had a similar ratio of the BCR rate (p = 0.172) but ISUP grade > 3 (p = 0.002; HR 2.689) was a significant BCR predictor. These results indicate that PSA and pathological status are key factors influencing PSM and BCR.


2014 ◽  
pp. 150127063130004 ◽  
Author(s):  
Andrew J. Lightfoot ◽  
Yu-Kai Su ◽  
Shailen Shivam Sehgal ◽  
Ziho Lee ◽  
Giovanni H. Greaves ◽  
...  

2020 ◽  
Vol 14 (4) ◽  
pp. 663-675 ◽  
Author(s):  
Antonio Benito Porcaro ◽  
Alessandro Tafuri ◽  
Marco Sebben ◽  
Nelia Amigoni ◽  
Aliasger Shakir ◽  
...  

2013 ◽  
Vol 7 (11-12) ◽  
pp. 711
Author(s):  
Allen Chang ◽  
Armen Derboghossians ◽  
Jennifer Kaswick ◽  
Brian Kim ◽  
Howard Jung ◽  
...  

Background: Initiating a robotics program is complex, in regards to achieving favourable outcomes, effectively utilizing an expensive surgical tool, and granting console privileges to surgeons. We report the implementation of a community-based robotics program among minimally-invasive surgery (MIS) urologists with and without formal robotics training.Methods: From August 2008 to December 2010 at Kaiser Permanente Southern California, 2 groups of urologists performing robot-assisted radical prostatectomy (RARP) were followed since the time of robot acquisition at a single institution. The robotics group included 4 surgeons with formal robotics training and the laparoscopic group with another 4 surgeons who were robot-naïve, but skilled in laparoscopy. The laparoscopic group underwent an initial 7-day mentorship period. Surgical proficiency was measured by various operative and pathological outcome variables. Data were evaluated using comparative statistics and multivariate analysis.Results: A total of 420 and 549 RARPs were performed by the robotics and laparoscopic groups, respectively. Operative times were longer in the laparoscopic group (p = 0.002), but estimated blood loss was similar. The robotics group had a significantly better overall positive surgical margin rate of 19.9% compared to the laparoscopic group (27.8%) (p = 0.005). Both groups showed improvements in operative and pathological parameters as they accrued experience, and achieved similar results towards the end of the study.Conclusions: Robot-naïve laparoscopic surgeons may achieve similar outcomes to robotic surgeons relatively early after a graduated mentorship period. This study may apply to a community-based practice in which multiple urologists with varied training backgrounds are granted robot privileges.


2017 ◽  
Vol 11 (11) ◽  
pp. E409-13 ◽  
Author(s):  
Anthony F. Adili ◽  
Julia Di Giovanni ◽  
Emma Kolesar ◽  
Nathan C. Wong ◽  
Jen Hoogenes ◽  
...  

Introduction: Since its introduction, robot-assisted laparoscopic radical prostatectomy (RARP) has gained widespread popularity, but is associated with a variable learning curve. Herein, we report the positive surgical margin (PSM) rates during the RARP learning curve of a single surgeon with significant previous laparoscopic radical prostatectomy (LRP) experience.Methods: We performed a prospective cohort study of the first 400 men with prostate cancer treated with RARP by a single surgeon (BS) with significant LRP experience. Our primary outcome was the impact of case timing in the learning curve on margin status. Our analysis was conducted by dividing the case numbers into quartiles (Q1‒Q4) and determining if a case falling into an earlier quartile had an impact on margin status relative to the most recent quartile (Q4).Results: The Q1 cases had an odds ratio for margin positivity of 1.74 compared to Q4 (p=0.1). Multivariate logistic regression did not demonstrate case number to be a significant predictor of PSM. The mean Q1 operative time was 207.4 minutes, decreasing to 179.2 by Q4 (p<0.0001). The mean Q1 estimated blood loss was 255.1 ml, decreasing to 213.6 by Q4 (p=0.0064). There was no change in length of hospitalization within the study period.Conclusions: Even when controlling for copredictors, a statistically significant learning curve for PSM rate of a surgeon with significant previous LRP experience was not detected during the first 400 RARP cases. We hypothesize that previous LRP experience may reduce the RARP PSM learning curve.


2015 ◽  
Vol 29 (6) ◽  
pp. 634-639 ◽  
Author(s):  
Andrew J. Lightfoot ◽  
Yu-Kai Su ◽  
Shailen S. Sehgal ◽  
Ziho Lee ◽  
Giovanni H. Greaves ◽  
...  

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