Evidence map›Paper›PMID 40922841›Full record

ReviewCureus2025

Simulation-Based Training in Aortic Aneurysm Surgery: Toward a New Educational Standard.

Abubakar I Sidik, Maxim L Khavandeev, Vladislav Dontsov, Dmitriy A Filimonov, Grigorii Esion, Malik K Al-Ariki, Md Limon Hossain, Mst Asia Ajgar Bithi, Nelson Nicolas, Salehk Amro Zuhair Salah

Abstract readReview
In one paragraph

Review in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Abubakar I SidikCardiovascular Surgery, Peoples' Friendship University of Russia, Moscow, RUS.
Maxim L KhavandeevCardiothoracic Surgery, Gusak Institute of Emergency and Reconstructive Surgery, Donetsk, RUS.
Vladislav DontsovCardiothoracic Surgery, Moscow Regional Research and Clinical Institute, Moscow, RUS.
Dmitriy A FilimonovExperimental Surgery, Gusak Institute of Emergency and Reconstructive Surgery, Donetsk, RUS.
Grigorii EsionCardiothoracic Surgery, A.A. Vishnevskiy Hospital, Moscow, RUS.
Malik K Al-ArikiSurgery, Peoples' Friendship University of Russia, Moscow, RUS.
Md Limon HossainCardiology, I.M. Sechenov First Moscow State Medical University, Moscow, RUS.
Mst Asia Ajgar BithiCardiovascular Medicine, Peoples' Friendship University of Russia, Moscow, RUS.
Nelson NicolasCardiovascular Medicine, Peoples' Friendship University of Russia, Moscow, RUS.
Salehk Amro Zuhair SalahCardiovascular Medicine, Moscow Multidisciplinary Clinical Center Kommunarka, Moscow, RUS.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Simulation-based training is transforming the education of vascular surgeons in the management of aortic aneurysms (AAs), addressing limitations in traditional apprenticeship models amid declining open surgical volumes and increasing reliance on complex endovascular techniques. This review explores the current landscape of simulation technologies, including computational modeling, fluid-structure interaction, patient-specific 3D printing, artificial intelligence, and robotic platforms. These tools enable high-fidelity, anatomically accurate, and physiologically realistic training environments. Validated simulations enhance surgical decision-making, device deployment strategies, and complication management without risk to patients. Despite barriers such as cost, variability in implementation, and limited outcome data, simulation holds promise as an essential component of future vascular surgery curricula. By combining technical innovation with personalized, data-driven training, simulation is poised to redefine competency development and improve surgical safety and efficacy.

Indexed as

aortic aneurysmendovascular aneurysm repairrobotic-assisted surgerysimulation-based trainingsurgical educationvirtual reality

Identifiers

PMID40922841
PMCPMC12414441

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.