Cover Image

The impact of a structured intensive modular training in the learning curve of robot assisted radical prostatectomy

Riccardo Schiavina, Marco Borghesi, Hussam Dababneh, Martina Sofia Rossi, Cristian Vincenzo Pultrone, Valerio Vagnoni, Francesco Chessa, Lorenzo Bianchi, Angelo Porreca, Alexandre Mottrie, Eugenio Brunocilla
  • Riccardo Schiavina
    University of Bologna, S. Orsola-Malpighi Hospital, Dept. of Urology, Bologna; Department of Experimental, Diagnostic and Specialty Medicine (DIMES), Cardio-Nephro-Thoracic Sciences Doctorate, University of Bologna, Italy
  • Marco Borghesi
    University of Bologna, S. Orsola-Malpighi Hospital, Dept. of Urology, Bologna; Department of Experimental, Diagnostic and Specialty Medicine (DIMES), Cardio-Nephro-Thoracic Sciences Doctorate, University of Bologna, Italy
  • Hussam Dababneh
    University of Bologna, S. Orsola-Malpighi Hospital, Dept. of Urology, Bologna, Italy
  • Martina Sofia Rossi
    University of Bologna, S. Orsola-Malpighi Hospital, Dept. of Urology, Bologna, Italy
  • Cristian Vincenzo Pultrone
    University of Bologna, S. Orsola-Malpighi Hospital, Dept. of Urology, Bologna; Department of Experimental, Diagnostic and Specialty Medicine (DIMES), Cardio-Nephro-Thoracic Sciences Doctorate, University of Bologna, Italy
  • Valerio Vagnoni
    University of Bologna, S. Orsola-Malpighi Hospital, Dept. of Urology, Bologna, Italy
  • Lorenzo Bianchi
    University of Bologna, S. Orsola-Malpighi Hospital, Dept. of Urology, Bologna, Italy
  • Angelo Porreca
    Policlinico Di Abano, Dept. of Urology, Abano Terme, Italy
  • Alexandre Mottrie
    OLV Robotic Surgery Institute, Aalst, Belgium
  • Eugenio Brunocilla
    University of Bologna, S. Orsola-Malpighi Hospital, Dept. of Urology, Bologna; Department of Experimental, Diagnostic and Specialty Medicine (DIMES), Cardio-Nephro-Thoracic Sciences Doctorate, University of Bologna, Italy

Abstract

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.

Keywords

Training; Robot assisted radical prostatectomy

Full Text:

PDF
Submitted: 2017-09-18 18:55:32
Published: 2018-03-31 00:00:00
Search for citations in Google Scholar
Related articles: Google Scholar
Abstract views:
170

Views:
PDF
47

Article Metrics

Metrics Loading ...

Metrics powered by PLOS ALM


Copyright (c) 2018 Francesco Chessa

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
 
© PAGEPress 2008-2018     -     PAGEPress is a registered trademark property of PAGEPress srl, Italy.     -     VAT: IT02125780185     •     Privacy