Literature DB >> 24051580

Transoral robotic surgery: simulation-based standardized training.

Ning Zhang1, Baran D Sumer.   

Abstract

IMPORTANCE: Simulation-based standardized training is important for the clinical training of physicians practicing robotic surgery.
OBJECTIVE: To train robotic surgery-naïve student volunteers using the da Vinci Skills Simulator (dVSS) for transoral robotic surgery (TORS).
DESIGN: Prospective inception cohort in 2012.
SETTING: Academic referral center. PARTICIPANTS: Sixteen medical student volunteers lacking experience in robotic surgery.
INTERVENTIONS: Participants trained with the dVSS in 12 exercises until competent, defined as an overall score of at least 91%. After a 1-, 3-, 5-, or 7-week postinitial training hiatus (n = 4 per group), participants reachieved competence on follow-up. MAIN OUTCOMES AND MEASURES: Total training time (TTT) to achieve competency, total follow-up time (TFT) to reachieve competency, and performance metrics.
RESULTS: All participants became competent. The TTT distribution was normal based on the Anderson-Darling normality test (P > .50), but our sample was divided into a short training time (STT) group (n = 10 [63%]) and long training time (LTT) group (n = 6 [37%]). The mean (SD) TTT was 2.4 (0.6) hours for the STT group and 4.7 (0.5) hours for the LTT group. All participants reachieved competence with a mean TFT that was significantly shorter than TTT. There was no significant difference between STT and LTT in mean TFT at 1 and 3 weeks (P = .79), but the LTT group had a longer TFT at 5 and 7 weeks (P = .04) but with no difference in final follow-up scores (P = .12). CONCLUSIONS AND RELEVANCE: Physicians in training can acquire robotic surgery competency. Participants who acquire skills faster regain robotic skills faster after a training hiatus, but, on retraining, all participants can regain equivalent competence. This information provides a benchmark for a simulator training program.

Entities:  

Mesh:

Year:  2013        PMID: 24051580     DOI: 10.1001/jamaoto.2013.4720

Source DB:  PubMed          Journal:  JAMA Otolaryngol Head Neck Surg        ISSN: 2168-6181            Impact factor:   6.223


  8 in total

Review 1.  Current state of virtual reality simulation in robotic surgery training: a review.

Authors:  Justin D Bric; Derek C Lumbard; Matthew J Frelich; Jon C Gould
Journal:  Surg Endosc       Date:  2015-08-25       Impact factor: 4.584

2.  An introductory curriculum for residents on transoral robotic surgery.

Authors:  Andrea Moglia
Journal:  J Robot Surg       Date:  2018-12-07

3.  Using virtual reality to maintain surgical skills during periods of robotic surgery inactivity.

Authors:  Loredana M Guseila; Archana Saranathan; Eric L Jenison; Karen M Gil; John J Elias
Journal:  J Robot Surg       Date:  2014-04-29

4.  Introductory TORS training in an otolaryngology residency program.

Authors:  Judd H Fastenberg; Marc J Gibber; Richard V Smith
Journal:  J Robot Surg       Date:  2018-02-07

5.  Evaluation of a 3D-Printed Transoral Robotic Surgery Simulator Utilizing Artificial Tissue.

Authors:  Alexander T Murr; Catherine J Lumley; Richard H Feins; Trevor G Hackman
Journal:  Laryngoscope       Date:  2021-12-09       Impact factor: 2.970

6.  Robotics in otolaryngology and head and neck surgery: Recommendations for training and credentialing: A report of the 2015 AHNS education committee, AAO-HNS robotic task force and AAO-HNS sleep disorders committee.

Authors:  Neil D Gross; F Christopher Holsinger; J Scott Magnuson; Umamaheswar Duvvuri; Eric M Genden; Tamer Ah Ghanem; Kathleen L Yaremchuk; David Goldenberg; Matthew C Miller; Eric J Moore; Luc Gt Morris; James Netterville; Gregory S Weinstein; Jeremy Richmon
Journal:  Head Neck       Date:  2016-03-07       Impact factor: 3.147

7.  Advanced head and neck surgery training during the COVID-19 pandemic.

Authors:  Babak Givi; Michael G Moore; Arnaud F Bewley; Charles S Coffey; Marc A Cohen; Amy C Hessel; Scharukh Jalisi; Steven Kang; Jason G Newman; Liana Puscas; Maisie Shindo; Andrew Shuman; Punam Thakkar; Donald T Weed; Ara Chalian
Journal:  Head Neck       Date:  2020-05-08       Impact factor: 3.147

8.  Virtual reality suturing task as an objective test for robotic experience assessment.

Authors:  Michael A Liss; Christopher J Kane; Tony Chen; Joel Baumgartner; Ithaar H Derweesh
Journal:  BMC Urol       Date:  2015-07-03       Impact factor: 2.264

  8 in total

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