Surgical Endoscopy

, Volume 27, Issue 7, pp 2638–2643

Robotic single-site hysterectomy: feasibility, learning curve and surgical outcome

  • V. Cela
  • L. Freschi
  • G. Simi
  • M. Ruggiero
  • R. Tana
  • N. Pluchino
New Technology

Abstract

Background

The field of laparoscopy has undergone several changes to improve the morbidity and cosmesis of laparoscopic surgery. The robotic single-site surgery is the inevitable hybridization of robotic technology with laparoendoscopic single-site surgery.

Methods

Perioperative information of 12 robotic single-site hysterectomies (R-SSH) were collected to evaluate the surgical feasibility and the possible influence of the body mass index (BMI) and the uterine weight on operative times.

Results

The mean operative time was 85 ± 33 min (range, 355 to 149 min), the mean docking time was 9 ± 3 min, and the mean console time was 76 ± 33 min. The mean blood loss was 80 ± 18 mL, and the median weight of resected uteri was 220 ± 45 g. No serious postoperative complications occurred. The CUSUM learning curve was observed to consist of two different phases: phase 1 (the initial 6 cases) and phase 2 (the last 6 cases) with significant reduction in operative and console time observed between the two phases. For BMI, no correlation was found with operative times, console times, and docking times, and no correlation was found between uterine weight and operative time.

Conclusions

This series, identifying two different phases of the learning curve and suggesting that the initial learning phase for the procedure can be achieved after six cases, confirms the feasibility and safety of a robotic approach for single-site hysterectomy. However, the limits of this study mainly rely on the limited casuistic and short follow-up, although the preliminary results appear promising. Larger series and prospective studies comparing R-SSH hysterectomy with standard robotic multiport hysterectomy are necessary to define properly the role of this innovative surgical technique.

Keywords

Single-site Robotic Feasibility Learning curve Hysterectomy 

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • V. Cela
    • 1
  • L. Freschi
    • 1
  • G. Simi
    • 1
  • M. Ruggiero
    • 1
  • R. Tana
    • 1
  • N. Pluchino
    • 1
  1. 1.Division of Gynecology and ObstetricsUniversity of PisaPisaItaly

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