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Learning Curves in Pediatric Robot-Assisted Pyeloplasty: A Systematic Review

Background: Robot-assisted surgery demands a specific skillset of surgical knowledge, skills, and attitudes from the robotic surgeon to function as part of the robotic team and for maximal utility of the assistive surgical robot. Subsequently, the learning process of robot-assisted surgery entails n...

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Autores principales: Pakkasjärvi, Niklas, Krishnan, Nellai, Ripatti, Liisi, Anand, Sachit
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9737296/
https://www.ncbi.nlm.nih.gov/pubmed/36498510
http://dx.doi.org/10.3390/jcm11236935
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author Pakkasjärvi, Niklas
Krishnan, Nellai
Ripatti, Liisi
Anand, Sachit
author_facet Pakkasjärvi, Niklas
Krishnan, Nellai
Ripatti, Liisi
Anand, Sachit
author_sort Pakkasjärvi, Niklas
collection PubMed
description Background: Robot-assisted surgery demands a specific skillset of surgical knowledge, skills, and attitudes from the robotic surgeon to function as part of the robotic team and for maximal utility of the assistive surgical robot. Subsequently, the learning process of robot-assisted surgery entails new modes of learning. We sought to systematically summarize the published data on pediatric robot-assisted pyeloplasty (pRALP) to decipher the learning process by analyzing learning curves. Methods: This review followed the PRISMA guidelines. PubMed, EMBASE, Web of Science, and Scopus databases were systematically searched for ‘learning curve’ AND ‘pediatric pyeloplasty’. All studies presenting outcomes of learning curves (LC) in the context of pRALP in patients < 18 years of age were included. Studies comparing LC in pRALP versus open and/or laparoscopic pyeloplasty were also included; however, those solely focusing on LC in non-robotic approaches were excluded. The methodological quality was assessed using the Newcastle and Ottawa scale. Results: Competency was non-uniformly defined in all fifteen studies addressing learning curves in pRALP. pRALP was considered safe at all stages. Proficiency in pRALP was reached after 18 cases, while competency was estimated to demand 31 operated cases with operative duration as outcome variable. Conclusions: Pediatric RALP is safe during the learning process and ‘learning by doing’ improves efficiency. Competencies with broader implications than time must be defined for future studies.
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spelling pubmed-97372962022-12-11 Learning Curves in Pediatric Robot-Assisted Pyeloplasty: A Systematic Review Pakkasjärvi, Niklas Krishnan, Nellai Ripatti, Liisi Anand, Sachit J Clin Med Systematic Review Background: Robot-assisted surgery demands a specific skillset of surgical knowledge, skills, and attitudes from the robotic surgeon to function as part of the robotic team and for maximal utility of the assistive surgical robot. Subsequently, the learning process of robot-assisted surgery entails new modes of learning. We sought to systematically summarize the published data on pediatric robot-assisted pyeloplasty (pRALP) to decipher the learning process by analyzing learning curves. Methods: This review followed the PRISMA guidelines. PubMed, EMBASE, Web of Science, and Scopus databases were systematically searched for ‘learning curve’ AND ‘pediatric pyeloplasty’. All studies presenting outcomes of learning curves (LC) in the context of pRALP in patients < 18 years of age were included. Studies comparing LC in pRALP versus open and/or laparoscopic pyeloplasty were also included; however, those solely focusing on LC in non-robotic approaches were excluded. The methodological quality was assessed using the Newcastle and Ottawa scale. Results: Competency was non-uniformly defined in all fifteen studies addressing learning curves in pRALP. pRALP was considered safe at all stages. Proficiency in pRALP was reached after 18 cases, while competency was estimated to demand 31 operated cases with operative duration as outcome variable. Conclusions: Pediatric RALP is safe during the learning process and ‘learning by doing’ improves efficiency. Competencies with broader implications than time must be defined for future studies. MDPI 2022-11-24 /pmc/articles/PMC9737296/ /pubmed/36498510 http://dx.doi.org/10.3390/jcm11236935 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Systematic Review
Pakkasjärvi, Niklas
Krishnan, Nellai
Ripatti, Liisi
Anand, Sachit
Learning Curves in Pediatric Robot-Assisted Pyeloplasty: A Systematic Review
title Learning Curves in Pediatric Robot-Assisted Pyeloplasty: A Systematic Review
title_full Learning Curves in Pediatric Robot-Assisted Pyeloplasty: A Systematic Review
title_fullStr Learning Curves in Pediatric Robot-Assisted Pyeloplasty: A Systematic Review
title_full_unstemmed Learning Curves in Pediatric Robot-Assisted Pyeloplasty: A Systematic Review
title_short Learning Curves in Pediatric Robot-Assisted Pyeloplasty: A Systematic Review
title_sort learning curves in pediatric robot-assisted pyeloplasty: a systematic review
topic Systematic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9737296/
https://www.ncbi.nlm.nih.gov/pubmed/36498510
http://dx.doi.org/10.3390/jcm11236935
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