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

Niklas Pakkasjärvi1, Nellai Krishnan2, Liisi Ripatti1

  • 1Department of Pediatric Surgery, Turku University Hospital, 20521 Turku, Finland.

Journal of Clinical Medicine
|December 11, 2022
PubMed
Summary

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Pediatric robot-assisted pyeloplasty (pRALP) is safe during the learning curve, with proficiency achieved around 18 cases. Defining broader competencies beyond operative time is crucial for future research in robotic surgery learning.

Area of Science:

  • Pediatric surgery
  • Robotic surgery
  • Surgical education

Background:

  • Robot-assisted surgery requires specialized skills for optimal team function and robot utilization.
  • The learning process for robot-assisted procedures necessitates novel educational approaches.
  • Pediatric robot-assisted pyeloplasty (pRALP) presents unique learning curve considerations.

Purpose of the Study:

  • To systematically review and analyze learning curves in pediatric robot-assisted pyeloplasty (pRALP).
  • To decipher the learning process and identify key milestones for pRALP proficiency.
  • To assess the safety and efficiency of pRALP during the learning phase.

Main Methods:

  • Systematic literature search following PRISMA guidelines across major databases (PubMed, EMBASE, Web of Science, Scopus).
Keywords:
learning curvepediatric urologypyeloplastyrobot-assisted surgerysurgical learning

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  • Inclusion of studies on learning curves (LC) in pRALP for patients under 18.
  • Methodological quality assessment using the Newcastle-Ottawa scale.

    • Main Results:

    • Fifteen studies were included, with non-uniform definitions of competency.
    • pRALP demonstrated safety across all learning stages.
    • Proficiency was observed after approximately 18 cases, with competency estimated at 31 cases, primarily using operative duration as the metric.

    Conclusions:

    • Pediatric RALP is a safe procedure during the learning process.
    • The principle of 'learning by doing' enhances efficiency in pRALP.
    • Future studies should define competencies beyond operative time for a comprehensive understanding of the learning curve.