Evidence map›Paper›PMID 33394090›Full record

ArticleWorld journal of urology2021

Endoscopic surgical simulation using low-fidelity and virtual reality transurethral resection simulators in urology simulation boot camp course: trainees feedback assessment study.

Christopher Berridge, Mithun Kailavasan, Grigorios Athanasiadis, Agapios Gkentzis, Tariq Tassadaq, Victor Palit, Bhavan Rai, Chandra S Biyani, Ghulam Nabi

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Article in World journal of urology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.9field-weighted citation impact, top 15% of its field
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

9 citing papers in PubMed, 13 citations in OpenAlex.

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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

9 authors at 7 institutions in 1 country.

Christopher BerridgeLeicester General Hospital, Leicester, UK.
Mithun KailavasanLeicester General Hospital, Leicester, UK.
Grigorios AthanasiadisAberdeen Royal Infirmary, Aberdeen, UK.
Agapios GkentzisRoyal Bolton Hospital, Bolton, UK.
Tariq TassadaqBedford General Hospital, Bedford, UK.
Victor PalitConsultant Urologist & Hon Senior Lecturer, Department of Urology, St James's University Hospital, Leeds Teaching Hospitals NHS Trust, Beckett Street, Leeds, LS9 7TF, UK.
Bhavan RaiFreeman Hospital, Newcastle, UK.
Chandra S BiyaniConsultant Urologist & Hon Senior Lecturer, Department of Urology, St James's University Hospital, Leeds Teaching Hospitals NHS Trust, Beckett Street, Leeds, LS9 7TF, UK. shekharbiyani@hotmail.com.ORCID http://orcid.org/0000-0003-3443-8425
Ghulam NabiUniversity of Dundee, Dundee, Scotland, UK.
Leeds Teaching Hospitals NHS Trust · GBLeicester General Hospital · GBAberdeen Royal Infirmary · GBBedford Hospital · GBFreeman Hospital · GBRoyal Bolton Hospital · GBUniversity of Dundee · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe objective of our study was to study trainees' feedback and rating of models for training transurethral resection of bladder lesions (TURBT) and prostate (TURP) during simulation.

methodsThe study was performed during the ''Transurethral resection (TUR) module" at the boot camp held in 2019. Prior to the course, all trainees were required to evaluate their experience in performing TURBT and TURP procedures. Trainees simulated resection on two different models; low-fidelity tissue model (Samed, GmBH, Dresden, Germany) and virtual reality simulator (TURPMentor, 3D Systems, Littleton, US). Following the completion of the module, trainees completed a questionnaire using a 5-point Likert scale to evaluate their assessment of the models for surgical training.

resultsIn total, 174 simulation assessments were performed by 56 trainees (Samed Bladder-40, Prostate-45, TURPMentor Bladder-51, Prostate-37). All trainees reported that they had performed < 50 TUR procedures. The Samed model median scores were for appearance (4/5), texture (5/5), feel (5/5) and conductibility (5/5). The TURPMentor median score was for appearance (4/5), texture and feel (4/5) and conductibility (4/5). The most common criticism of the Samed model was that it failed to mimic bleeding. In contrast, trainees felt that the TURPMentor haptic feedback was inadequate to allow for close resection and did not calibrate movements accurately.

conclusionsOur results demonstrate that both forms of simulators (low-fidelity and virtual reality) were rated highly by urology trainees and improve their confidence in performing transurethral resection and in fact complement each other in providing lower tract endoscopic resection simulation.

Indexed as

Models, AnatomicUrologic Surgical ProceduresAttitude of Health PersonnelClinical CompetenceComputer SimulationFeedbackHumansMaleProstatic NeoplasmsSimulation TrainingUrinary Bladder NeoplasmsUrologyVirtual RealitySimulationTURBTTURPUrologyVirtual reality

Identifiers

PMID33394090
OpenAlexW3118398921

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.