Evidence map›Paper›PMID 32232016›Full record

ReviewResearch and reports in urology2020

Current Status of Simulation Training in Urology: A Non-Systematic Review.

Andrei Adrian Kozan, Luke Huiming Chan, Chandra Shekhar Biyani

Abstract readReview
In one paragraph

Review in Research and reports in urology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–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

19 citing papers in PubMed.

  1. Article
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  10. Review
  11. Review
  12. Article
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  14. Validity of the Rezum Simulator for Trainees.Acta informatica medica : AIM : journal of the Society for Medical Informatics of Bosnia & Herzegovina : casopis Drustva za medicinsku informatiku BiH · 2023
    Article
  15. Article
  16. Innovations in Urologic Surgical Training.Current urology reports · 2021
    Review
  17. Review
  18. Review
  19. Article
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

3 authors.

Andrei Adrian KozanDepartment of Urology, Hull University Teaching Hospitals NHS Trust, Castle Hill Hospital, Cottingham, UK.ORCID 0000-0001-7318-5489
Luke Huiming ChanDepartment of Urology, Sheffield Teaching Hospitals NHS Foundation Trust, Royal Hallamshire Hospital, Sheffield, UK.
Chandra Shekhar BiyaniDepartment of Urology, The Leeds Teaching Hospitals NHS Trust, St James's University Hospital, Leeds, UK.ORCID 0000-0003-3443-8425

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Simulation has emerged as an effective solution to increasing modern constraints in surgical training. It is recognized that a larger proportion of surgical complications occur during the surgeon's initial learning curve. The simulation takes the learning curve out of the operating theatre and facilitates training in a safe and pressure-free environment whilst focusing on patient safety. The cost of simulation is not insignificant and requires commitment in funding, human resources and logistics. It is therefore important for trainers to have evidence when selecting various simulators or devices. Our non-systematic review aims to provide a comprehensive up-to-date picture on urology simulators and the evidence for their validity. It also discusses emerging technologies and future directions. Urologists should embed evidence-based simulation in training programs to shorten learning curves while maintaining patient safety and work should be directed toward a validated and agreed curriculum.

Indexed as

educationinnovationlearningsimulationskillsurology

Identifiers

PMID32232016
PMCPMC7085342

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.