Learning Curve of Robot-Assisted Thymectomy: Single Surgeon's 7-Year Experience.

CUSUM analysis learning curve myasthenia gravis rat robot-assisted thymectomy thymectomy

Journal

Frontiers in surgery
ISSN: 2296-875X
Titre abrégé: Front Surg
Pays: Switzerland
ID NLM: 101645127

Informations de publication

Date de publication:
2022
Historique:
received: 23 01 2022
accepted: 16 06 2022
entrez: 29 8 2022
pubmed: 30 8 2022
medline: 30 8 2022
Statut: epublish

Résumé

Robot-assisted thymectomy (RAT) has rapidly emerged as the preferred approach over open trans-sternal or video-assisted thoracoscopy for the surgical treatment of thymomas and non-thymomatous myasthenia gravis (MG). The aim of this study was to describe and discuss the learning curve (LC) of a single surgeon performing 113 consecutive RATs. A single-center retrospective analysis of prospectively collected clinical data was performed on all patients who had been operated on by the same surgeon in an RAT setting between October 2013 and February 2020. The cumulative sum (CUSUM) analysis of the operative time was used to define the completion of the learning curve (CLC) in RAT. The CLC was separately calculated for myasthenic patients, non-myasthenic patients, and docking time. In myasthenic patients, the CLC cut-off was found in 19 patients. Considering the CLC cut-off of 19 patients, the mean operative time in phase 1 (first 19 cases) was 229.79 ± 93.40 min, while it was 167.35 ± 41.63 min in phase 2 (last 51 cases), According to our data, LC in RAT seems to be steep, and RAT confirms to be safe even before reaching CLC.

Sections du résumé

Background UNASSIGNED
Robot-assisted thymectomy (RAT) has rapidly emerged as the preferred approach over open trans-sternal or video-assisted thoracoscopy for the surgical treatment of thymomas and non-thymomatous myasthenia gravis (MG). The aim of this study was to describe and discuss the learning curve (LC) of a single surgeon performing 113 consecutive RATs.
Methods UNASSIGNED
A single-center retrospective analysis of prospectively collected clinical data was performed on all patients who had been operated on by the same surgeon in an RAT setting between October 2013 and February 2020. The cumulative sum (CUSUM) analysis of the operative time was used to define the completion of the learning curve (CLC) in RAT. The CLC was separately calculated for myasthenic patients, non-myasthenic patients, and docking time.
Results UNASSIGNED
In myasthenic patients, the CLC cut-off was found in 19 patients. Considering the CLC cut-off of 19 patients, the mean operative time in phase 1 (first 19 cases) was 229.79 ± 93.40 min, while it was 167.35 ± 41.63 min in phase 2 (last 51 cases),
Conclusions UNASSIGNED
According to our data, LC in RAT seems to be steep, and RAT confirms to be safe even before reaching CLC.

Identifiants

pubmed: 36034391
doi: 10.3389/fsurg.2022.860899
pmc: PMC9415802
doi:

Types de publication

Journal Article

Langues

eng

Pagination

860899

Informations de copyright

Copyright © 2022 Meacci, Nachira, Congedo, Petracca-Ciavarella, Vita, Porziella, Chiappetta, Lococo, Tabacco, Triumbari and Margaritora.

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.

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Auteurs

Elisa Meacci (E)

Dipartimento di Medicina e Chirurgia Traslazionale, Università Cattolica del Sacro Cuore, Roma, Italy.

Dania Nachira (D)

Dipartimento di Medicina e Chirurgia Traslazionale, Università Cattolica del Sacro Cuore, Roma, Italy.

Maria Teresa Congedo (MT)

Dipartimento di Medicina e Chirurgia Traslazionale, Università Cattolica del Sacro Cuore, Roma, Italy.

Leonardo Petracca-Ciavarella (L)

Dipartimento di Medicina e Chirurgia Traslazionale, Università Cattolica del Sacro Cuore, Roma, Italy.

Maria Letizia Vita (ML)

Dipartimento di Medicina e Chirurgia Traslazionale, Università Cattolica del Sacro Cuore, Roma, Italy.

Venanzio Porziella (V)

Dipartimento di Medicina e Chirurgia Traslazionale, Università Cattolica del Sacro Cuore, Roma, Italy.

Marco Chiappetta (M)

Dipartimento di Medicina e Chirurgia Traslazionale, Università Cattolica del Sacro Cuore, Roma, Italy.

Filippo Lococo (F)

Dipartimento di Medicina e Chirurgia Traslazionale, Università Cattolica del Sacro Cuore, Roma, Italy.

Diomira Tabacco (D)

Dipartimento di Medicina e Chirurgia Traslazionale, Università Cattolica del Sacro Cuore, Roma, Italy.

Elizabeth Katherine Anna Triumbari (EKA)

Nuclear Medicine Unit, TracerGLab, Department of Radiology, Radiotherapy and Hematology, Fondazione Policlinico Universitario A. Gemelli, IRCCS, Roma, Italy.

Stefano Margaritora (S)

Dipartimento di Medicina e Chirurgia Traslazionale, Università Cattolica del Sacro Cuore, Roma, Italy.

Classifications MeSH