Assessment of learning curve and oncologic feasibility of robotic pancreaticoduodenectomy: A propensity score‐based comparison with open approach

Author(s):  
Hyeyeon Kim ◽  
Seo Young Park ◽  
Yejong Park ◽  
Jaewoo Kwon ◽  
Woohyung Lee ◽  
...  
2020 ◽  
Vol 49 (6) ◽  
pp. 377-383
Author(s):  
Brian KP Goh ◽  
Roxanne Y Teo

Despite the potential clinical advantages offered by laparoscopic pancreatic surgery (LPS), the main obstacle to its widespread adoption is the technically demanding nature of the procedure and its steep learning curve. LPS and robotic pancreatic surgery (RPS) have been proven to result in superior short-term perioperative outcomes and equivalent long-term oncological outcomes compared to the conventional open approach, with the caveat that they are performed by expert surgeons who have been trained to perform such procedures. The primary challenge faced by most pancreatic surgeons is the steep learning curve associated with these complex procedures and the need to undergo surgical training, especially with regards to laparoscopic and robotic pancreaticoduodenectomy. Current evidence suggests that RPS may help to shorten the lengthy learning curve required for LPS. More robust evidence—in the form of large randomised controlled trials—is needed to determine whether LPS and RPS can be safely adopted universally. Ann Acad Med Singapore 2020;49:377–83 Key words: Laparoscopic pancreatectomy, Laparoscopic pancreaticoduodenectomy, Minimally invasive pancreatic surgery, Robotic pancreatectomy, Robotic pancreaticoduodenectomy


2018 ◽  
Vol 90 (1) ◽  
pp. 1 ◽  
Author(s):  
Riccardo Schiavina ◽  
Marco Borghesi ◽  
Hussam Dababneh ◽  
Martina Sofia Rossi ◽  
Cristian Vincenzo Pultrone ◽  
...  

Aim: The success of Robot Assisted Laparoscopic Prostatectomy (RALP) is mainly due to his relatively short learning curve. Twenty cases are needed to reach a “4 hours-proficiency”. However, to achieve optimal functional outcomes such as urinary continence and potency recovery may require more experience. We aim to report the perioperative and early functional outcomes of patients undergoing RALP, after a structured modular training program. Methods: A surgeon with no previous laparoscopic or robotic experience attained a 3 month modular training including: a) e-learning; b) assistance and training to the operating table; c) dry console training; d) step by step in vivo modular training performing 40 surgical steps in increasing difficulty, under the supervision of an experienced mentor. Demographics, intraoperative and postoperative functional outcomes were recorded after his first 120 procedures, considering four groups of 30 cases. Results: All procedures were completed successfully without conversion to open approach. Overall 19 (15%) post operative complications were observed and 84% were graded as minor (Clavien I-II). Overall operative time and console time gradually decreased during the learning curve, with statistical significance in favour of Group 4. The overall continence rate at 1 and 3 months was 74% and 87% respectively with a significant improvement in continence rate throughout the four groups (p = 0.04). Considering those patients submitted to nerve-sparing procedure we found a significant increase in potency recovery over the four groups (p = 0.04) with the higher potency recovery rate up to 80% in the last 30 cases. Conclusions: Optimal perioperative and functional outcomes have been attained since early phase of the learning curve after an intensive structured modular training and less than 100 consecutive procedures seem needed in order to achieve optimal urinary continence and erectile function recovery.


2019 ◽  
Vol 18 (1) ◽  
pp. e794-e795
Author(s):  
A. Olivero ◽  
A. Galfano ◽  
S. Secco ◽  
M. Piccinelli ◽  
D. Panarello ◽  
...  

HPB ◽  
2020 ◽  
Vol 22 ◽  
pp. S132
Author(s):  
B.R. Harris ◽  
K.A. Musgrove ◽  
M.E. Hogg ◽  
J.W. Marsh ◽  
H.J. Zeh ◽  
...  

HPB ◽  
2016 ◽  
Vol 18 ◽  
pp. e101
Author(s):  
M.U. Butt ◽  
H. Osman ◽  
H. Aderianwalla ◽  
R. Hellums ◽  
S. Furlough ◽  
...  

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