Consensus for Thoracoscopic Lower Lobectomy: Essential Components and Targets for Simulation.

Document Type

Article

Publication Date

11-2022

Publication Title

Annals of Thoracic Surgery

Abstract

BACKGROUND: Despite demonstration of its clear benefits relative to open approaches, a video-assisted thoracic surgery technique for pulmonary lobectomy has not been universally adopted. This study aims to overcome potential barriers by establishing the essential components of the operation and determining which steps are most useful for simulation training.

METHODS: After randomly selecting experienced thoracic surgeons to participate, an initial list of components to a lower lobectomy was distributed. Feedback was provided by the participants, and modifications were made based on anonymous responses in a Delphi process. Components were declared essential once at least 80% of participants came to an agreement. The steps were then rated based on cognitive and technical difficulty followed by listing the components most appropriate for simulation.

RESULTS: After 3 rounds of voting 18 components were identified as essential to performance of a video-assisted thoracic surgery for lower lobectomy. The components deemed the most difficult were isolation and division of the basilar and superior segmental branches of the pulmonary artery, isolation and division of the lower lobe bronchus, and dissection of lymphovascular tissue to expose the target bronchus. The steps determined to be most amenable for simulation were isolation and division of the branches of the pulmonary artery, the lower lobe bronchus, and the inferior pulmonary vein.

CONCLUSIONS: Using a Delphi process a list of essential components for a video-assisted thoracic surgery for lower lobectomy was established. Furthermore 3 components were identified as most appropriate for simulation-based training, providing insights for future simulation development.

Volume

114

Issue

5

First Page

1895

Last Page

1901

DOI

10.1016/j.athoracsur.2021.09.033

ISSN

1552-6259

PubMed ID

34688617

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