Evidence map›Paper›PMID 38958718›Full record

Trial reportSurgical endoscopy2024

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

Julia E Menso, A Masie Rahimi, Maurice J W Zwart, Freek Daams, Joey de Hondt, Emir Karadza, Roberto M Montorsi, Felix Nickel, H Jaap Bonjer, Els J M Nieveen van Dijkum and 1 more

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Surgical endoscopy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Review
  5. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Julia E MensoAmsterdam UMC, Department of Surgery, Location University of Amsterdam, Amsterdam, the Netherlands.ORCID 0000-0002-3398-6879
A Masie RahimiAmsterdam UMC, Department of Surgery, Location University of Amsterdam, Amsterdam, the Netherlands.
Maurice J W ZwartAmsterdam UMC, Department of Surgery, Location University of Amsterdam, Amsterdam, the Netherlands.
Freek DaamsCancer Center Amsterdam, Amsterdam, the Netherlands.
Joey de HondtAmsterdam UMC, Department of Surgery, Location University of Amsterdam, Amsterdam, the Netherlands.
Emir KaradzaDepartment of General, Visceral and Transplantation Surgery, Heidelberg University Hospital, Heidelberg, Germany.
Roberto M MontorsiAmsterdam UMC, Department of Surgery, Location University of Amsterdam, Amsterdam, the Netherlands.
Felix NickelDepartment of General, Visceral and Transplantation Surgery, Heidelberg University Hospital, Heidelberg, Germany.
H Jaap BonjerCancer Center Amsterdam, Amsterdam, the Netherlands.
Els J M Nieveen van DijkumAmsterdam UMC, Department of Surgery, Location University of Amsterdam, Amsterdam, the Netherlands.
Marc G BesselinkAmsterdam UMC, Department of Surgery, Location University of Amsterdam, Amsterdam, the Netherlands. m.g.besselink@amsterdamUMC.nl.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRobotic 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.

methodsThis was a randomized controlled crossover trial conducted with 20 robotic novices from 3 countries who underwent robotic suturing training using an Intuitive Surgical

resultsOverall, 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.

conclusionSurgical 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.

Indexed as

Clinical CompetenceCross-Over StudiesRobotic Surgical ProceduresSimulation TrainingSuture TechniquesAdultFemaleHumansJejunostomyLiverMaleRobotic simulation trainingRobotic surgeryRobotic suturingSimNow simulatorTraining

Identifiers

PMID38958718
PMCPMC11362386

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.