Evidence map›Paper›PMID 29796313›Full record

ReviewMinimally invasive surgery2018

Microvascular Anastomosis Training in Neurosurgery: A Review.

Vadim A Byvaltsev, Serik K Akshulakov, Roman A Polkin, Sergey V Ochkal, Ivan A Stepanov, Yerbol T Makhambetov, Talgat T Kerimbayev, Michael Staren, Evgenii Belykh, Mark C Preul

Abstract readReview
In one paragraph

Review in Minimally invasive surgery, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
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  10. Synthesis of a novel monofilament bioabsorbable suture for biomedical applications.Journal of biomedical materials research. Part B, Applied biomaterials · 2022
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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

10 authors.

Vadim A ByvaltsevIrkutsk State Medical University, Krasnogo Vosstaniya St. 1, Irkutsk, Russia.ORCID 0000-0003-4349-7101
Serik K AkshulakovNational Center of Neurosurgery, 34/1 Turan Av., Astana, Kazakhstan.
Roman A PolkinIrkutsk State Medical University, Krasnogo Vosstaniya St. 1, Irkutsk, Russia.
Sergey V OchkalIrkutsk State Medical University, Krasnogo Vosstaniya St. 1, Irkutsk, Russia.
Ivan A StepanovIrkutsk State Medical University, Krasnogo Vosstaniya St. 1, Irkutsk, Russia.
Yerbol T MakhambetovNational Center of Neurosurgery, 34/1 Turan Av., Astana, Kazakhstan.
Talgat T KerimbayevNational Center of Neurosurgery, 34/1 Turan Av., Astana, Kazakhstan.
Michael StarenDepartment of Neurosurgery Research, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, 350 West Thomas Road, Phoenix, AZ 85013, USA.
Evgenii BelykhIrkutsk State Medical University, Krasnogo Vosstaniya St. 1, Irkutsk, Russia.ORCID 0000-0003-2060-5739
Mark C PreulDepartment of Neurosurgery Research, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, 350 West Thomas Road, Phoenix, AZ 85013, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cerebrovascular diseases are among the most widespread diseases in the world, which largely determine the structure of morbidity and mortality rates. Microvascular anastomosis techniques are important for revascularization surgeries on brachiocephalic and carotid arteries and complex cerebral aneurysms and even during resection of brain tumors that obstruct major cerebral arteries. Training in microvascular surgery became even more difficult with less case exposure and growth of the use of endovascular techniques. In this text we will briefly discuss the history of microvascular surgery, review current literature on simulation models with the emphasis on their merits and shortcomings, and describe the views and opinions on the future of the microvascular training in neurosurgery. In "dry" microsurgical training, various models created from artificial materials that simulate biological tissues are used. The next stage in training more experienced surgeons is to work with nonliving tissue models. Microvascular training using live models is considered to be the most relevant due to presence of the blood flow. Training on laboratory animals has high indicators of face and constructive validity. One of the future directions in the development of microsurgical techniques is the use of robotic systems. Robotic systems may play a role in teaching future generations of microsurgeons. Modern technologies allow access to highly accurate learning environments that are extremely similar to real environment. Additionally, assessment of microsurgical skills should become a fundamental part of the current evaluation of competence within a microneurosurgical training program. Such an assessment tool could be utilized to ensure a constant level of surgical competence within the recertification process. It is important that this evaluation be based on validated models.

Identifiers

PMID29796313
PMCPMC5896222

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LicenceCC BY
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Registered trials

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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.