Literature DB >> 31055610

A live porcine model for robotic sacrocolpopexy training.

Khushabu Kasabwala1, Ramy Goueli1, Patrick J Culligan2.   

Abstract

INTRODUCTION AND HYPOTHESIS: Robotic sacrocolpopexy is an effective and durable technique for pelvic organ prolapse repair. However, the learning curve for this procedure has underscored the need for an effective surgical training module. Given the cost, infection risk, poor tissue compliance, and scarcity of human cadavers, the live porcine model represents a realistic, available, and cost-effective alternative. This article describes a live porcine model for teaching robotic sacrocolpopexy to determine whether it teaches key aspects of live human robotic sacrocolpopexy to the learner.
METHODS: This robotic sacrocolpopexy model was created using the Da Vinci Xi or Si robotic system on domestic pigs under general anesthesia. The main steps of the model include: (1) creating the porcine "cervix" and (2) performing robotic sacrocolpopexy. The model was evaluated with a survey given to 18 board-certified surgeons who attended the training course between December 2016 and April 2018.
RESULTS: All of the participants reported improvements in their economy of motion, tissue handling ability, suturing efficiency, and overall performance of robotic sacrocolpopexy. Furthermore, a majority of participants were likely to incorporate aspects of the model into their practice (88.8%) and recommend the model to colleagues (94.2%).
CONCLUSIONS: The porcine model provides a feasible tool for teaching robotic sacrocolpopexy to physicians.

Entities:  

Keywords:  Pelvic organ prolapse; Porcine model; Robotic sacrocolpopexy; Robotic surgery; Surgical training

Mesh:

Year:  2019        PMID: 31055610     DOI: 10.1007/s00192-019-03936-7

Source DB:  PubMed          Journal:  Int Urogynecol J        ISSN: 0937-3462            Impact factor:   2.894


  7 in total

1.  Assessing the learning curve of robotic sacrocolpopexy.

Authors:  Brian J Linder; Mallika Anand; Amy L Weaver; Joshua L Woelk; Christopher J Klingele; Emanuel C Trabuco; John A Occhino; John B Gebhart
Journal:  Int Urogynecol J       Date:  2015-08-21       Impact factor: 2.894

2.  Construct Validity of a Simple Laparoscopic Ovarian Cystectomy Model Using a Validated Objective Structured Assessment of Technical Skills.

Authors:  Elizabeth Britton Chahine; Chan Hee Han; Tamika Auguste
Journal:  J Minim Invasive Gynecol       Date:  2017-05-17       Impact factor: 4.137

Review 3.  Robot-assisted sacrocolpopexy for pelvic organ prolapse: a systematic review and meta-analysis of comparative studies.

Authors:  Maurizio Serati; Giorgio Bogani; Paola Sorice; Andrea Braga; Marco Torella; Stefano Salvatore; Stefano Uccella; Antonella Cromi; Fabio Ghezzi
Journal:  Eur Urol       Date:  2014-03-06       Impact factor: 20.096

4.  Teaching Vaginal Hysterectomy via Simulation: Creation and Validation of the Objective Skills Assessment Tool for Simulated Vaginal Hysterectomy on a Task Trainer and Performance Among Different Levels of Trainees.

Authors:  D R Malacarne; C M Escobar; C J Lam; K L Ferrante; D Szyld; Veronica T Lerner
Journal:  Female Pelvic Med Reconstr Surg       Date:  2019 Jul/Aug       Impact factor: 2.091

5.  Validation of the Simulated Vaginal Hysterectomy Trainer.

Authors:  Monique H Vaughan; Shunaha Kim-Fine; Kathie L Hullfish; Tovia M Smith; Nazema Y Siddiqui; Elisa R Trowbridge
Journal:  J Minim Invasive Gynecol       Date:  2018-03-07       Impact factor: 4.137

6.  Evaluation of the porcine model to teach various ancillary procedures to gynecologic oncology fellows.

Authors:  Mitchel S Hoffman; Leo E Ondrovic; Robert M Wenham; Sachin M Apte; Murray L Shames; Emanuel E Zervos; William S Weinberg; William S Roberts
Journal:  Am J Obstet Gynecol       Date:  2009-07       Impact factor: 8.661

Review 7.  History and future of human cadaver preservation for surgical training: from formalin to saturated salt solution method.

Authors:  Shogo Hayashi; Munekazu Naito; Shinichi Kawata; Ning Qu; Naoyuki Hatayama; Shuichi Hirai; Masahiro Itoh
Journal:  Anat Sci Int       Date:  2015-09-01       Impact factor: 1.741

  7 in total

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