Evidence map›Paper›PMID 28765716›Full record

ReviewAdvances in medical education and practice2017

Simulation training in neurosurgery: advances in education and practice.

Sanjay Konakondla, Reginald Fong, Clemens M Schirmer

Abstract readReview
In one paragraph

Review in Advances in medical education and practice, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Virtual Reality in Neurosurgery: Beyond Neurosurgical Planning.International journal of environmental research and public health · 2022
    Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
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  15. 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

3 authors.

Sanjay KonakondlaDepartment of Neurosurgery and Neuroscience Institute, Geisinger Medical Center, Geisinger Health System, Danville, PA, USA.
Reginald FongDepartment of Neurosurgery and Neuroscience Institute, Geisinger Medical Center, Geisinger Health System, Danville, PA, USA.
Clemens M SchirmerDepartment of Neurosurgery and Neuroscience Institute, Geisinger Medical Center, Geisinger Health System, Danville, PA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The current simulation technology used for neurosurgical training leaves much to be desired. Significant efforts are thoroughly exhausted in hopes of developing simulations that translate to give learners the "real-life" feel. Though a respectable goal, this may not be necessary as the application for simulation in neurosurgical training may be most useful in early learners. The ultimate uniformly agreeable endpoint of improved outcome and patient safety drives these investments. We explore the development, availability, educational taskforces, cost burdens and the simulation advancements in neurosurgical training. The technologies can be directed at achieving early resident milestones placed by the Accreditation Council for Graduate Medical Education. We discuss various aspects of neurosurgery disciplines with specific technologic advances of simulation software. An overview of the scholarly landscape of the recent publications in the realm of medical simulation and virtual reality pertaining to neurologic surgery is provided. We analyze concurrent concept overlap between PubMed headings and provide a graphical overview of the associations between these terms.

Indexed as

ACGMEhaptic feedbackneurosurgery trainingresidency educationsimulationtask analysisvirtual reality

Identifiers

PMID28765716
PMCPMC5524176

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.