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Updated: May 14, 2026

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Learning Curve of Docking Time in Robot-Assisted Radical Prostatectomy with the Hugo RAS System: How Many Procedures

Andrea Iannuzzi1, Alberto Ragusa2, Alessandro De Giuseppe1

  • 1Research Unit of Urology, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, 00128 Rome, Italy.

Journal of Clinical Medicine
|May 13, 2026
PubMed
Summary

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The Hugo RAS System, a new robotic platform, requires only a few procedures to achieve optimal docking times. This indicates a rapid learning curve for surgeons using this innovative system.

Area of Science:

  • Urology
  • Robotic Surgery
  • Surgical Technology

Background:

  • The Hugo RAS System is a novel robotic platform with a modular design.
  • Understanding the learning curve for new robotic systems is crucial for efficient surgical workflow.

Purpose of the Study:

  • To determine the number of consecutive robotic-assisted radical prostatectomies (RARP) needed for optimal docking time with the Hugo RAS System.
  • To evaluate the learning curve associated with the Hugo RAS System's docking procedure.

Main Methods:

  • Analysis of data from 68 patients undergoing RARP using the Hugo RAS System.
  • Univariate linear regression and cumulative sum (CUSUM) analysis to assess the relationship between procedure number and docking time.

Main Results:

Keywords:
Hugo RASRARPdocking timeradical prostatectomy

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Last Updated: May 14, 2026

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  • A significant negative correlation was found between the number of procedures and docking time (p < 0.0017).
  • CUSUM analysis indicated that optimal docking time was achieved around the sixth procedure.
  • Median docking time was 5 minutes (IQR 4-13).

Conclusions:

  • The Hugo RAS System demonstrates a rapid learning curve for docking.
  • Optimal docking times can be achieved with a limited number of procedures, not significantly impacting overall surgical duration.