Simulation in Perioperative Liver Transplant Anesthesia: A Systematic Review.

anesthesia education liver transplant liver transplant anesthesiologist medical residency peri-operative care simulation surgery

Journal

Cureus
ISSN: 2168-8184
Titre abrégé: Cureus
Pays: United States
ID NLM: 101596737

Informations de publication

Date de publication:
Jun 2022
Historique:
accepted: 02 06 2022
entrez: 7 7 2022
pubmed: 8 7 2022
medline: 8 7 2022
Statut: epublish

Résumé

Due to the complexity of liver transplant patients and the variability in exposure to transplantation by anesthesia trainees, simulation is often required as an adjunct to clinical experience. This systematic review identifies current simulation models in the literature that pertain to perioperative liver transplant anesthesia. Data were collected by performing an electronic search of the PubMed and Scopus databases for articles describing simulation in transplant anesthesia. Abstracts were screened using the preferred reporting items for systematic reviews and meta-analysis (PRISMA) guidelines. Three reviewers analyzed 16 abstracts found in the search and agreed upon articles that met the inclusion criteria for the systematic review. A total of five publications met the inclusion criteria; they could be grouped as cognitive skills and technical skills simulators. Cognitive skills simulators utilized high-fidelity mannequins and animal models combined with traditional educational material to enhance pattern recognition of critical complications during liver transplantation. One manuscript focused on a technical skills acquisition by utilizing transesophageal echocardiography (TEE) to identify intraoperative pathologies. There is a heterogeneity in the exposure to liver transplant care during anesthesia training. Simulation provides low-stakes exposure to the high-stakes skills required in the operating room. Hence, it can be used as an adjunct to improve both cognitive and technical skill acquisition for perioperative transplant anesthesia. The goal of these simulation programs is to improve patient outcomes and produce more capable anesthesiologists.

Identifiants

pubmed: 35795521
doi: 10.7759/cureus.25602
pmc: PMC9250322
doi:

Types de publication

Journal Article Review

Langues

eng

Pagination

e25602

Informations de copyright

Copyright © 2022, Oh et al.

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

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Auteurs

Thomas Oh (T)

General Surgery, University of Texas (UT) Health San Antonio, San Antonio, USA.

Ronit Patnaik (R)

General Surgery, University of Texas (UT) Health San Antonio, San Antonio, USA.

Jacob Buckner (J)

General Surgery, University of Texas (UT) Health San Antonio, San Antonio, USA.

Lucijana Krokar (L)

General Surgery, University of Texas (UT) Health San Antonio, San Antonio, USA.

Azan Ibrahim (A)

General Surgery, University of Texas (UT) Health San Antonio, San Antonio, USA.

Rehana S Lovely (RS)

Physiology and Anatomy, University of North Texas (UNT) Health Science Center, Fort Worth, USA.

Mustafa T Khan (MT)

General Surgery, University of Texas (UT) Health San Antonio, San Antonio, USA.

Classifications MeSH