Simulation-Based Medical Education and Training Enhance Anesthesia Residents' Proficiency in Erector Spinae Plane Block.

erector spinae plane (ESP) block high fidelity simulation improved proficiency medical education resident training ultrasound-guided regional anesthesia

Journal

Frontiers in medicine
ISSN: 2296-858X
Titre abrégé: Front Med (Lausanne)
Pays: Switzerland
ID NLM: 101648047

Informations de publication

Date de publication:
2022
Historique:
received: 06 02 2022
accepted: 21 03 2022
entrez: 25 4 2022
pubmed: 26 4 2022
medline: 26 4 2022
Statut: epublish

Résumé

Advances in regional anesthesia and pain management led to the advent of ultrasound-guided fascial plane blocks, which represent a new and promising route for the administration of local anesthetics. Both practical and theoretical knowledge of locoregional anesthesia are therefore becoming fundamental, requiring specific training programs for residents. Simulation-based medical education and training (SBET) has been recently applied to ultrasound-guided regional anesthesia (UGRA) with remarkable results. With this in mind, the anesthesia and intensive care residency program of the University of Milano-Bicocca organized a 4-h regional anesthesia training workshop with the BlockSim Fifty-two first-year anesthesia residents were exposed to a 4-h training workshop focused on peripheral blocks. The course included an introductory theoretical session held by a locoregional anesthetist expert, a practical training on human models and mannequins using Onvision The time needed to achieve the block during the second attempt was significantly shorter (131 [83, 198] vs. 68 [27, 91] s, A 4-h hands-on course based on SBET may enhance first-year residents' UGRA ability, decrease the number of punctures and time needed to perform the ESP block, and improve the correct aim of the fascia.

Sections du résumé

Background UNASSIGNED
Advances in regional anesthesia and pain management led to the advent of ultrasound-guided fascial plane blocks, which represent a new and promising route for the administration of local anesthetics. Both practical and theoretical knowledge of locoregional anesthesia are therefore becoming fundamental, requiring specific training programs for residents. Simulation-based medical education and training (SBET) has been recently applied to ultrasound-guided regional anesthesia (UGRA) with remarkable results. With this in mind, the anesthesia and intensive care residency program of the University of Milano-Bicocca organized a 4-h regional anesthesia training workshop with the BlockSim
Methods UNASSIGNED
Fifty-two first-year anesthesia residents were exposed to a 4-h training workshop focused on peripheral blocks. The course included an introductory theoretical session held by a locoregional anesthetist expert, a practical training on human models and mannequins using Onvision
Results UNASSIGNED
The time needed to achieve the block during the second attempt was significantly shorter (131 [83, 198] vs. 68 [27, 91] s,
Conclusions UNASSIGNED
A 4-h hands-on course based on SBET may enhance first-year residents' UGRA ability, decrease the number of punctures and time needed to perform the ESP block, and improve the correct aim of the fascia.

Identifiants

pubmed: 35463012
doi: 10.3389/fmed.2022.870372
pmc: PMC9024057
doi:

Types de publication

Journal Article

Langues

eng

Pagination

870372

Informations de copyright

Copyright © 2022 Torrano, Zadek, Bugada, Cappelleri, Russo, Tinti, Giorgi, Langer and Fumagalli.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Références

Anaesthesia. 2021 Jan;76 Suppl 1:110-126
pubmed: 33426660
Anaesthesia. 2020 Jan;75 Suppl 1:e101-e110
pubmed: 31903582
Anaesthesia. 2021 Aug;76(8):1129-1133
pubmed: 34224138
Anaesthesia. 2020 Mar;75(3):293-297
pubmed: 31268173
Minerva Anestesiol. 2021 Jun;87(6):738-739
pubmed: 33591151
Best Pract Res Clin Anaesthesiol. 2019 Dec;33(4):573-581
pubmed: 31791572
Reg Anesth Pain Med. 2018 May;43(4):341-346
pubmed: 29561295
Acta Anaesthesiol Scand. 2019 Sep;63(8):1055-1062
pubmed: 31037724
Korean J Anesthesiol. 2019 Feb;72(1):13-23
pubmed: 30481945
Reg Anesth Pain Med. 2020 Aug;45(8):634-639
pubmed: 32540878
Curr Opin Anaesthesiol. 2014 Dec;27(6):610-5
pubmed: 25225825
Reg Anesth Pain Med. 2009 Jan-Feb;34(1):40-6
pubmed: 19258987
Anaesthesia. 2021 Jan;76 Suppl 1:3-7
pubmed: 33426654
Scand J Pain. 2021 May 14;21(4):671-679
pubmed: 33984888
Curr Opin Anaesthesiol. 2018 Oct;31(5):643-648
pubmed: 29994940
Anesth Analg. 2021 Sep 1;133(3):772-780
pubmed: 34232953
J Ultrasound Med. 2015 Oct;34(10):1883-93
pubmed: 26384608
Anaesthesia. 2021 Jan;76 Suppl 1:53-64
pubmed: 33426656
Reg Anesth Pain Med. 2012 Jan-Feb;37(1):51-4
pubmed: 22179300

Auteurs

Vito Torrano (V)

Department of Medicine and Surgery, University of Milan-Bicocca, Monza, Italy.
Department of Anesthesia and Intensive Care Medicine, Niguarda Ca' Granda, Milan, Italy.

Francesco Zadek (F)

Department of Medicine and Surgery, University of Milan-Bicocca, Monza, Italy.

Dario Bugada (D)

Department of Emergency and Critical Care Medicine, Azienda Socio Sanitaria Territoriale Papa Giovanni XXIII, Bergamo, Italy.

Gianluca Cappelleri (G)

Anesthesia and Intensive Care Unit, Policlinico di Monza, Monza, Italy.

Gianluca Russo (G)

Department of Emergency and Urgency, Azienda Socio Sanitaria Territoriale Lodi, Lodi, Italy.

Giulia Tinti (G)

Department of Medicine and Surgery, University of Milan-Bicocca, Monza, Italy.

Antonio Giorgi (A)

Department of Medicine and Surgery, University of Milan-Bicocca, Monza, Italy.

Thomas Langer (T)

Department of Medicine and Surgery, University of Milan-Bicocca, Monza, Italy.
Department of Anesthesia and Intensive Care Medicine, Niguarda Ca' Granda, Milan, Italy.

Roberto Fumagalli (R)

Department of Medicine and Surgery, University of Milan-Bicocca, Monza, Italy.
Department of Anesthesia and Intensive Care Medicine, Niguarda Ca' Granda, Milan, Italy.

Classifications MeSH