Evidence map›Paper›PMID 39071766›Full record

ArticlePlastic and reconstructive surgery. Global open2024

Synthetic Simulators for Microsurgery Training: A Systematic Review.

Gianluca Sapino, Stephanie Gonvers, Mario Cherubino, Alberto Ballestín, Pietro Giovanni di Summa

Abstract read
In one paragraph

Article in Plastic and reconstructive surgery. Global open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

Gianluca SapinoFrom the Department of Plastic, Reconstructive, Aesthetic and Hand Surgery, University Hospital of Lausanne (CHUV), University of Lausanne, Lausanne, Switzerland.
Stephanie GonversFrom the Department of Plastic, Reconstructive, Aesthetic and Hand Surgery, University Hospital of Lausanne (CHUV), University of Lausanne, Lausanne, Switzerland.
Mario CherubinoDepartment of Plastic and Hand Surgery, University Hospital of Varese, University of Varese, Varese, Italy.
Alberto BallestínTumor Microenvironment Laboratory, UMR3347 CNRS/U1021 INSERM, Institut Curie, Orsay-Paris, France.
Pietro Giovanni di SummaFrom the Department of Plastic, Reconstructive, Aesthetic and Hand Surgery, University Hospital of Lausanne (CHUV), University of Lausanne, Lausanne, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Microsurgery has a steep learning curve. Synthetic simulators have proven to be useful training tools for the initial learning stages, as well as being ethically sound, viable, safe, and cost-effective. The objective of this review was to determine the quality, effectiveness, and validity of these simulators as well as to assess their ability to evaluate microsurgical skills. Methods: A systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines was performed. We searched databases (Web of Science, Scopus, and PubMed) to identify original articles describing synthetic training models for microsurgery. Three reviewers evaluated articles for inclusion following predefined selection criteria. Data were extracted from full-texts of included articles. Results: Thirty-nine studies met the inclusion criteria. A total of 38 different devices have been recorded. Microsurgical training devices offer a low-cost, fast, and consistent method to concretely quantify and assess the initial microsurgical skills of trainees using standardized exercises that can be scored by the examiner. According to the authors, the outcomes were satisfactory, with a tangible improvement in microsurgical abilities, despite the lack of a common comparison scale. Conclusions: Thanks to their availability, cost, and effectiveness, synthetic models are the recommended option to train basic, intermediate and advanced procedures before executing them on in vivo models.

Identifiers

PMID39071766
PMCPMC11281774

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LicenceCC BY-NC-ND
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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.