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The PD-ROBOSCORE

Authors :
Niccolò Napoli
Concetta Cacace
Emanuele F. Kauffmann
Leia Jones
Michael Ginesini
Cesare Gianfaldoni
Alice Salamone
Fabio Asta
Allegra Ripolli
Armando Di Dato
Olivier R. Busch
Marie L. Cappelle
Ying Jui Chao
Roeland F. de Wilde
Thilo Hackert
Jin-Young Jang
Bas Groot Koerkamp
Wooil Kwon
Daan Lips
Misha D.P. Luyer
Felix Nickel
Olivier Saint-Marc
Yan-Shen Shan
Baiyong Shen
Fabio Vistoli
Marc G. Besselink
Mohammad Abu Hilal
Ugo Boggi
Graduate School
Surgery
CCA - Cancer Treatment and Quality of Life
AGEM - Amsterdam Gastroenterology Endocrinology Metabolism
CCA - Imaging and biomarkers
Source :
Surgery (United States), 173(6), 1438-1446. Mosby Inc.
Publication Year :
2023

Abstract

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/m2 for males and ≥30 kg/m2 for females (odds ratio:2.39; P < .0001), borderline resectable tumor (odd ratio:1.98; P < .0001), uncinate process tumor (odds ratio:1.69; P < .0001), pancreatic duct size

Subjects

Subjects :
Surgery

Details

Language :
English
ISSN :
00396060
Volume :
173
Issue :
6
Database :
OpenAIRE
Journal :
Surgery (United States)
Accession number :
edsair.doi.dedup.....109abd13f48786c5d7b762508c10549f