The PD-ROBOSCORE: A difficulty score for robotic pancreatoduodenectomy.


Journal

Surgery
ISSN: 1532-7361
Titre abrégé: Surgery
Pays: United States
ID NLM: 0417347

Informations de publication

Date de publication:
06 2023
Historique:
received: 21 10 2022
revised: 12 02 2023
accepted: 22 02 2023
medline: 22 5 2023
pubmed: 28 3 2023
entrez: 27 3 2023
Statut: ppublish

Résumé

Difficulty scoring systems are important for the safe, stepwise implementation of new procedures. We designed a retrospective observational study for building a difficulty score for robotic pancreatoduodenectomy. The difficulty score (PD-ROBOSCORE) aims at predicting severe postoperative complications after robotic pancreatoduodenectomy. The PD-ROBOSCORE was developed in a training cohort of 198 robotic pancreatoduodenectomies and was validated in an international multicenter cohort of 686 robotic pancreatoduodenectomies. Finally, all centers tested the model during the early learning curve (n = 300). Growing difficulty levels (low, intermediate, high) were defined using cut-off values set at the 33rd and 66th percentile (NCT04662346). Factors included in the final multivariate model were a body mass index of ≥25 kg/m The PD-ROBOSCORE predicts severe postoperative complications after robotic pancreatoduodenectomy. The score is readily available via www.pancreascalculator.com.

Sections du résumé

BACKGROUND
Difficulty scoring systems are important for the safe, stepwise implementation of new procedures. We designed a retrospective observational study for building a difficulty score for robotic pancreatoduodenectomy.
METHODS
The difficulty score (PD-ROBOSCORE) aims at predicting severe postoperative complications after robotic pancreatoduodenectomy. The PD-ROBOSCORE was developed in a training cohort of 198 robotic pancreatoduodenectomies and was validated in an international multicenter cohort of 686 robotic pancreatoduodenectomies. Finally, all centers tested the model during the early learning curve (n = 300). Growing difficulty levels (low, intermediate, high) were defined using cut-off values set at the 33rd and 66th percentile (NCT04662346).
RESULTS
Factors included in the final multivariate model were a body mass index of ≥25 kg/m
CONCLUSION
The PD-ROBOSCORE predicts severe postoperative complications after robotic pancreatoduodenectomy. The score is readily available via www.pancreascalculator.com.

Identifiants

pubmed: 36973127
pii: S0039-6060(23)00109-5
doi: 10.1016/j.surg.2023.02.020
pii:
doi:

Banques de données

ClinicalTrials.gov
['NCT04662346']

Types de publication

Observational Study Multicenter Study Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1438-1446

Informations de copyright

Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.

Auteurs

Niccolò Napoli (N)

Division of General and Transplant Surgery, University of Pisa, Italy.

Concetta Cacace (C)

Division of General and Transplant Surgery, University of Pisa, Italy.

Emanuele F Kauffmann (EF)

Division of General and Transplant Surgery, University of Pisa, Italy.

Leia Jones (L)

Department of General Surgery, Istituto Ospedaliero Fondazione Poliambulanza, Brescia, Italy; Department of Surgery, Amsterdam UMC, University of Amsterdam, Netherlands; Cancer Center Amsterdam, Netherlands.

Michael Ginesini (M)

Division of General and Transplant Surgery, University of Pisa, Italy.

Cesare Gianfaldoni (C)

Division of General and Transplant Surgery, University of Pisa, Italy.

Alice Salamone (A)

Division of General and Transplant Surgery, University of Pisa, Italy.

Fabio Asta (F)

Division of General and Transplant Surgery, University of Pisa, Italy.

Allegra Ripolli (A)

Division of General and Transplant Surgery, University of Pisa, Italy.

Armando Di Dato (A)

Division of General and Transplant Surgery, University of Pisa, Italy.

Olivier R Busch (OR)

Department of Surgery, Amsterdam UMC, University of Amsterdam, Netherlands; Cancer Center Amsterdam, Netherlands.

Marie L Cappelle (ML)

Department of Surgery, Erasmus MC Cancer Institute, Rotterdam, Netherlands.

Ying Jui Chao (YJ)

Department of Surgery, College of Medicine, National Cheng Kung University Hospital, Tainan, Taiwan.

Roeland F de Wilde (RF)

Department of Surgery, Erasmus MC Cancer Institute, Rotterdam, Netherlands.

Thilo Hackert (T)

Department of General, Visceral, and Transplantation Surgery, Heidelberg University Hospital, Germany.

Jin-Young Jang (JY)

Department of Hepatobiliary and Pancreatic Surgery, Seoul National University College of Medicine, Seoul, South Korea.

Bas Groot Koerkamp (BG)

Department of Surgery, Erasmus MC Cancer Institute, Rotterdam, Netherlands.

Wooil Kwon (W)

Department of Hepatobiliary and Pancreatic Surgery, Seoul National University College of Medicine, Seoul, South Korea.

Daan Lips (D)

Department of Surgery, Medisch Spectrum Twente, Enschede, Netherlands.

Misha D P Luyer (MDP)

Department of Surgery, Catharina Hospital Eindhoven, Eindhoven, Netherlands.

Felix Nickel (F)

Department of General, Visceral, and Transplantation Surgery, Heidelberg University Hospital, Germany.

Olivier Saint-Marc (O)

Department of Surgery, Centre Hospitalier Regional D'Orleans, Orléans, France.

Yan-Shen Shan (YS)

Department of Surgery, College of Medicine, National Cheng Kung University Hospital, Tainan, Taiwan.

Baiyong Shen (B)

Department of General Surgery, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Fabio Vistoli (F)

Division of General and Transplant Surgery, University of Pisa, Italy.

Marc G Besselink (MG)

Department of Surgery, Amsterdam UMC, University of Amsterdam, Netherlands; Cancer Center Amsterdam, Netherlands.

Mohammad Abu Hilal (MA)

Department of General Surgery, Istituto Ospedaliero Fondazione Poliambulanza, Brescia, Italy.

Ugo Boggi (U)

Division of General and Transplant Surgery, University of Pisa, Italy. Electronic address: u.boggi@med.unipi.it.

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