Initial 50 consecutive full-robotic pancreatoduodenectomies without conversion by a single surgeon: a learning curve analysis from a tertiary referral high-volume center.

Da Vinci Xi Learning curve Pancreatic surgery Previous manual pancreatoduodenectomy Robotic pancreatoduodenectomy Robotic surgery

Journal

Surgical endoscopy
ISSN: 1432-2218
Titre abrégé: Surg Endosc
Pays: Germany
ID NLM: 8806653

Informations de publication

Date de publication:
05 2023
Historique:
received: 14 09 2022
accepted: 27 11 2022
medline: 5 5 2023
pubmed: 4 1 2023
entrez: 3 1 2023
Statut: ppublish

Résumé

Several studies report on a learning curve for robotic pancreatoduodenectomy (R-PD) ranging between 20 and 80 operations, with conversion rates varying between 1.1 and 35%. However, as these publications mostly refer to initial robotic experiences and do not take into account the previous surgical background in pancreatic surgery (PS) and in robotic-assisted surgery (RAS), the center's volume, as well as the platform used, we aimed to perform a surgical outcomes analysis with a particular view to these aspects. Intraoperative and perioperative outcomes of the first 50 consecutive R-PD performed with the da Vinci Xi by the same surgeon, within a tertiary referral high-volume center, between January 2018 and March 2022, were analyzed. The surgeon was previously experienced in both PS and RAS. Shewhart control chart and cumulative sum (CUSUM) analysis were used to evaluate the learning curve of R-PD. All the operations were performed with a full-robotic technique, without any conversion to open surgery. Twenty of 50 patients (40%) had a BMI ≥ 25 kg/m An extensive prior experience in both PS and RAS, within a tertiary referral high-volume center with availability of the da Vinci Xi platform, can significantly flatten the learning curve and, therefore, enable safe performance of challenging operations, i.e., pancreatoduodenectomies with a minimally invasive approach, with very low risk of conversion to open surgery, even in the first 50 operations.

Sections du résumé

BACKGROUND
Several studies report on a learning curve for robotic pancreatoduodenectomy (R-PD) ranging between 20 and 80 operations, with conversion rates varying between 1.1 and 35%. However, as these publications mostly refer to initial robotic experiences and do not take into account the previous surgical background in pancreatic surgery (PS) and in robotic-assisted surgery (RAS), the center's volume, as well as the platform used, we aimed to perform a surgical outcomes analysis with a particular view to these aspects.
METHODS
Intraoperative and perioperative outcomes of the first 50 consecutive R-PD performed with the da Vinci Xi by the same surgeon, within a tertiary referral high-volume center, between January 2018 and March 2022, were analyzed. The surgeon was previously experienced in both PS and RAS. Shewhart control chart and cumulative sum (CUSUM) analysis were used to evaluate the learning curve of R-PD.
RESULTS
All the operations were performed with a full-robotic technique, without any conversion to open surgery. Twenty of 50 patients (40%) had a BMI ≥ 25 kg/m
CONCLUSIONS
An extensive prior experience in both PS and RAS, within a tertiary referral high-volume center with availability of the da Vinci Xi platform, can significantly flatten the learning curve and, therefore, enable safe performance of challenging operations, i.e., pancreatoduodenectomies with a minimally invasive approach, with very low risk of conversion to open surgery, even in the first 50 operations.

Identifiants

pubmed: 36596929
doi: 10.1007/s00464-022-09784-9
pii: 10.1007/s00464-022-09784-9
pmc: PMC9810244
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

3531-3539

Informations de copyright

© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

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Auteurs

Luca Morelli (L)

General Surgery Unit, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Via Paradisa 2, 56125, Pisa, Italy.
Multidisciplinary Center of Robotic Surgery, University Hospital of Pisa, Pisa, Italy.
EndoCAS (Center for Computer Assisted Surgery), University of Pisa, Pisa, Italy.

Niccolò Furbetta (N)

General Surgery Unit, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Via Paradisa 2, 56125, Pisa, Italy.
Multidisciplinary Center of Robotic Surgery, University Hospital of Pisa, Pisa, Italy.

Matteo Palmeri (M)

General Surgery Unit, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Via Paradisa 2, 56125, Pisa, Italy.
Multidisciplinary Center of Robotic Surgery, University Hospital of Pisa, Pisa, Italy.

Simone Guadagni (S)

General Surgery Unit, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Via Paradisa 2, 56125, Pisa, Italy. s.guadagni@ao-pisa.toscana.it.
Multidisciplinary Center of Robotic Surgery, University Hospital of Pisa, Pisa, Italy. s.guadagni@ao-pisa.toscana.it.

Gregorio Di Franco (G)

General Surgery Unit, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Via Paradisa 2, 56125, Pisa, Italy.
Multidisciplinary Center of Robotic Surgery, University Hospital of Pisa, Pisa, Italy.

Desirée Gianardi (D)

General Surgery Unit, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Via Paradisa 2, 56125, Pisa, Italy.
Multidisciplinary Center of Robotic Surgery, University Hospital of Pisa, Pisa, Italy.

Rosa Cervelli (R)

Interventional Radiology Division, Imaging Department, Azienda Ospedaliera Universitaria Pisana, Pisa, Italy.

Valentina Lorenzoni (V)

Institute of Management, Scuola Superiore Sant'Anna, Pisa, Italy.

Annalisa Comandatore (A)

General Surgery Unit, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Via Paradisa 2, 56125, Pisa, Italy.
Multidisciplinary Center of Robotic Surgery, University Hospital of Pisa, Pisa, Italy.

Cristina Carpenito (C)

General Surgery Unit, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Via Paradisa 2, 56125, Pisa, Italy.
Multidisciplinary Center of Robotic Surgery, University Hospital of Pisa, Pisa, Italy.

Giulio Di Candio (G)

General Surgery Unit, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Via Paradisa 2, 56125, Pisa, Italy.
Multidisciplinary Center of Robotic Surgery, University Hospital of Pisa, Pisa, Italy.

Alfred Cuschieri (A)

Institute for Medical Science and Technology, University of Dundee, Dundee, Scotland, UK.

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