Literature DB >> 25357037

Robotic microsurgery: validating an assessment tool and plotting the learning curve.

Taiba Alrasheed1, Jun Liu, Matthew M Hanasono, Charles E Butler, Jesse C Selber.   

Abstract

BACKGROUND: The surgical robot has emerged as a potentially useful tool in microsurgery. The purpose of this study was to develop a validated assessment instrument and assess the learning curve for robotic microsurgery. The authors hypothesized that subjects would demonstrate improvement across multiple domains of performance with repetition of robotic microsurgical tasks.
METHODS: In part 1, a novel assessment instrument called the Structured Assessment of Robotic Microsurgical Skills was tested. Four blinded expert evaluators graded six robotic microsurgery videos and interrater reliability was determined. In part 2, a cohort of 10 participants at various skill levels performed five robotic microvascular anastomoses. All 50 sessions were subjected to blind evaluation using the assessment instrument. Primary outcome measures included changes in operative time over the five sessions, and changes in assessment scores for all skill areas.
RESULTS: Interrater reliability for the Structured Assessment of Robotic Microsurgical Skills instrument was excellent for each skill area, demonstrated by Cronbach alpha scores greater than 0.9 in each category across evaluators. All skill areas improved significantly for all participants, and operative time decreased for all participants over the course of the study. The results showed an initial steep ascent in technical skill acquisition followed by more gradual improvement, and a steady decrease in operative time to as short as 9 minutes.
CONCLUSIONS: The Structured Assessment of Robotic Microsurgery Skills is a valid instrument for assessing microsurgical skill. Subjects at all levels of training, ranging from minimal microsurgical experience to expert microsurgeons, gained proficiency over the course of five robotic sessions.

Entities:  

Mesh:

Year:  2014        PMID: 25357037     DOI: 10.1097/PRS.0000000000000550

Source DB:  PubMed          Journal:  Plast Reconstr Surg        ISSN: 0032-1052            Impact factor:   4.730


  7 in total

1.  Robotic-assisted microvascular surgery: skill acquisition in a rat model.

Authors:  Nicholas S Clarke; Johnathan Price; Travis Boyd; Stefano Salizzoni; Kenton J Zehr; Alejandro Nieponice; Pietro Bajona
Journal:  J Robot Surg       Date:  2017-08-10

Review 2.  What is the Learning Curve for Laparoscopic Major Hepatectomy?

Authors:  Kimberly M Brown; David A Geller
Journal:  J Gastrointest Surg       Date:  2016-03-08       Impact factor: 3.452

Review 3.  Microvascular Anastomosis Training in Neurosurgery: A Review.

Authors:  Vadim A Byvaltsev; Serik K Akshulakov; Roman A Polkin; Sergey V Ochkal; Ivan A Stepanov; Yerbol T Makhambetov; Talgat T Kerimbayev; Michael Staren; Evgenii Belykh; Mark C Preul
Journal:  Minim Invasive Surg       Date:  2018-03-28

4.  A Systematic Review of the Role of Robotics in Plastic and Reconstructive Surgery-From Inception to the Future.

Authors:  Thomas D Dobbs; Olivia Cundy; Harsh Samarendra; Khurram Khan; Iain Stuart Whitaker
Journal:  Front Surg       Date:  2017-11-15

Review 5.  Robotics in Cleft Surgery: Origins, Current Status and Future Directions.

Authors:  Yasser Al Omran; Ali Abdall-Razak; Nader Ghassemi; Samar Alomran; Ding Yang; Ali M Ghanem
Journal:  Robot Surg       Date:  2019-12-24

6.  Preliminary clinical experience of robot-assisted surgery in treatment with genioplasty.

Authors:  Li Lin; Cheng Xu; Yunyong Shi; Chaozheng Zhou; Ming Zhu; Gang Chai; Le Xie
Journal:  Sci Rep       Date:  2021-03-18       Impact factor: 4.379

Review 7.  Robotic-Assisted Microsurgery and Its Future in Plastic Surgery.

Authors:  Matthias M Aitzetmüller; Marie-Luise Klietz; Alexander F Dermietzel; Tobias Hirsch; Maximilian Kückelhaus
Journal:  J Clin Med       Date:  2022-06-13       Impact factor: 4.964

  7 in total

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