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Surgical Endoscopy
Article . 2024 . Peer-reviewed
License: CC BY
Data sources: Crossref
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PubMed Central
Other literature type . 2024
License: CC BY
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Robotic hepaticojejunostomy training in novices using robotic simulation and dry-lab suturing (ROSIM): randomized controlled crossover trial

Authors: Julia E. Menso; A. Masie Rahimi; Maurice J. W. Zwart; Freek Daams; Joey de Hondt; Emir Karadza; Roberto M. Montorsi; +4 Authors

Robotic hepaticojejunostomy training in novices using robotic simulation and dry-lab suturing (ROSIM): randomized controlled crossover trial

Abstract

Abstract Background Robotic suturing training is in increasing demand and can be done using suture-pads or robotic simulation training. Robotic simulation is less cumbersome, whereas a robotic suture-pad approach could be more effective but is more costly. A training curriculum with crossover between both approaches may be a practical solution. However, studies assessing the impact of starting with robotic simulation or suture-pads in robotic suturing training are lacking. Methods This was a randomized controlled crossover trial conducted with 20 robotic novices from 3 countries who underwent robotic suturing training using an Intuitive Surgical® X and Xi system with the SimNow (robotic simulation) and suture-pads (dry-lab). Participants were randomized to start with robotic simulation (intervention group, n = 10) or suture-pads (control group, n = 10). After the first and second training, all participants completed a robotic hepaticojejunostomy (HJ) in biotissue. Primary endpoint was the objective structured assessment of technical skill (OSATS) score during HJ, scored by two blinded raters. Secondary endpoints were force measurements and a qualitative analysis. After training, participants were surveyed regarding their preferences. Results Overall, 20 robotic novices completed both training sessions and performed 40 robotic HJs. After both trainings, OSATS was scored higher in the robotic simulation-first group (3.3 ± 0.9 vs 2.5 ± 0.8; p = 0.049), whereas the median maximum force (N) (5.0 [3.2–8.0] vs 3.8 [2.3–12.8]; p = 0.739) did not differ significantly between the groups. In the survey, 17/20 (85%) participants recommended to include robotic simulation training, 14/20 (70%) participants preferred to start with robotic simulation, and 20/20 (100%) to include suture-pad training. Conclusion Surgical performance during robotic HJ in robotic novices was significantly better after robotic simulation-first training followed by suture-pad training. A robotic suturing curriculum including both robotic simulation and dry-lab suturing should ideally start with robotic simulation.

Keywords

Male, Adult, Cross-Over Studies, Training ; Female [MeSH] ; SimNow simulator ; Jejunostomy/methods [MeSH] ; Robotic Surgical Procedures/education [MeSH] ; Adult [MeSH] ; Humans [MeSH] ; Robotic simulation training ; Article ; Male [MeSH] ; Cross-Over Studies [MeSH] ; Liver/surgery [MeSH] ; Robotic suturing ; Simulation Training/methods [MeSH] ; Clinical Competence [MeSH] ; Robotic surgery ; Jejunostomy/education [MeSH] ; Suture Techniques/education [MeSH], Suture Techniques, Jejunostomy, Article, Robotic Surgical Procedures, Liver, Humans, Female, Clinical Competence, Simulation Training

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Top 10%
Average
Average
Green
hybrid