Evidence map›Paper›PMID 31064080›Full record

ArticleDiagnostics (Basel, Switzerland)2019

Four Virtual-Reality Simulators for Diagnostic Abdominal Ultrasound Training in Radiology.

Mia Louise Østergaard, Lars Konge, Niklas Kahr, Elisabeth Albrecht-Beste, Michael Bachmann Nielsen, Kristina Rue Nielsen

Abstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Editorial.Ultrasound international open · 2019
    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

6 authors.

Mia Louise ØstergaardDepartment of Radiology, North Sealand Hospital, 3400 Hillerød, Denmark. mlo@dadlnet.dk.ORCID 0000-0001-8979-1176
Lars KongeCopenhagen Academy for Medical Education and Simulation, 2100 Copenhagen, Denmark. lars.konge@regionh.dk.
Niklas KahrDepartment of Radiology, Rigshospitalet, 2100 Copenhagen, Denmark. niklaskahr@gmail.com.
Elisabeth Albrecht-BesteDepartment of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, 2100 Copenhagen, Denmark. elisabeth.albrecht-beste@regionh.dk.
Michael Bachmann NielsenDepartment of Radiology, Rigshospitalet, 2100 Copenhagen, Denmark. mbn@dadlnet.dk.ORCID 0000-0002-9380-1688
Kristina Rue NielsenDepartment of Radiology, Rigshospitalet, 2100 Copenhagen, Denmark. marie.kristina.rue.nielsen.01@regionh.dk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ultrasound exams need skilled examiners, and simulation-based training could provide standardized and safe skill training. This study aims to give an overview of different types of virtual-reality simulators for use in abdominal diagnostic ultrasound training in radiology. Fifteen specialized radiologists and radiological residents were presented with two similar cases on four different simulators for abdominal ultrasound training. A feedback sheet for each individual simulator and for an overall comparison was filled out by all participants. All means of scores were compared, and simulators were ranked from least to most favorable. One simulator was ranked most favorable in seven out of nine questions, but none of the mean scores had statistically significant differences. All simulators were recommended for training radiologists, and all simulators were perceived to benefit trainees more than experienced ultra-sonographers.

Indexed as

abdominaleducationradiologysimulationultrasoundvirtual-reality

Identifiers

PMID31064080
PMCPMC6627565

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.