Journal of Clinical Medicine (Nov 2022)

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

  • Niklas Pakkasjärvi,
  • Nellai Krishnan,
  • Liisi Ripatti,
  • Sachit Anand

DOI
https://doi.org/10.3390/jcm11236935
Journal volume & issue
Vol. 11, no. 23
p. 6935

Abstract

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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 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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