Learning curve analysis of multiport robot-assisted hysterectomy

Global trends and hotspots in the learning curves of robotic-assisted surgery: a bibliometric and visualization analysis

In recent years, there has been a substantial increase in the number of research papers published in the field of robotic-assisted surgery (RAS). Nevertheless, systematic analyses focusing on the key hotspots associated with the learning curves (LCs) of RAS, global collaboration models, and future trends remain relatively limited. This study employed bibliometric methods to conduct a comprehensive search and analysis of papers on the LC of RAS published in the Web of Science Core Collection between 2005 and 2025. A visual analysis was performed across multiple dimensions, including countries, institutions, sources, and authors. The results revealed an upward trend in the number of publications, with a peak observed in 2024. The United States ranked first in terms of publication volume, while Yonsei University emerged as the most productive institution. Mottrie Alexandre contributed to the highest number of publications, and Dindo d received the highest number of citations. Frequently occurring keywords included "outcome", "experience", "minimally invasive surgery", "revision", and "laparoscopic surgery". Clustering keywords were associated with "rectal cancer", "en-y gastric bypass", "transoral robotic surgery", "spine surgery", and "endometrial cancer". Furthermore, the top five keywords with the strongest citation bursts were "laparoscopic radical prostatectomy", "total mesorectal excision", "da vinci", "prostatectomy", and "mrc clasicc trial". This study offers valuable insights into the future development of this field and supports further exploration and innovation.

Comparison between learning curves of robot-assisted and laparoscopic surgery in gynaecology: a systematic review

Background

The advantages and disadvantages of Robotic Laparoscopic Surgery (RLS) compared to other minimally invasive surgical approaches are debated in the literature.

Objective

To evaluate the learning curves (LC) and their assessment methods for Robotic Laparoscopic Surgery (RLS) and Laparoscopic Surgery (LPS) in gynaecologic procedures.

Materials and Methods

A systematic review of the literature was performed including the English language observational or interventional studies reporting the absolute number of procedures needed to achieve competency in RLS and LPS gynaecologic procedures, along with an objective and reproducible LC assessment method.

Main outcome measures

Number of procedures needed to achieve competency in RLS and LPS and LC assessment methods were extracted from included studies.

Results

Six studies with a total of 545 women were included. Several surgical procedures and methods for LC assessment were assessed in the included studies. For radical hysterectomy, bilateral salpingo-oophorectomy and lymph node dissection, the minimum number of procedures required to reach the LC was smaller in RLS than LPS in two studies out of four. For sacrocolpopexy, the number of procedures required to reach the LC was lower in RLS and LPS in one study out of two.

Conclusion

RLS learning curve was reported to be quicker than that of LPS for radical hysterectomy, bilateral salpingo-oophorectomy and lymph node dissection. However, a standardised and widely accepted method for LC assessment in endoscopic surgery is needed, as well as further randomised clinical trials, especially involving inexperienced surgeons.

What is new?

This study may be the first systematic review to evaluate the LCs and their assessment methods for RLS and LPS in gynaecologic procedures.

Robot-assisted laparoscopy does not have demonstrable advantages over conventional laparoscopy in endometriosis surgery: a systematic review and meta-analysis

BACKGROUND

Endometriosis is a chronic condition affecting 6-10% of women of reproductive age, with endometriosis-related pain and infertility being the leading symptoms. Currently, the gold standard treatment approach to surgery is conventional laparoscopy (CL); however, the increasing availability of robot-assisted surgery is projected as a competitor of CL. This study aimed to compare the perioperative outcomes of robot-assisted laparoscopy (RAL) and CL in endometriosis surgery.

OBJECTIVES

We aimed to compare the effectiveness and safety of these two procedures.

METHODS

A systematic search was conducted in three medical databases. Studies investigating different perioperative outcomes of endometriosis-related surgeries were included. Results are presented as odds ratios (OR) or mean differences (MD) with 95% confidence intervals (CI).

RESULTS

Our search yielded 2,014 records, of which 13 were eligible for data extraction. No significant differences were detected between the CL and RAL groups in terms of intraoperative complications (OR = 1.07, CI 0.43-2.63), postoperative complications (OR = 1.3, CI 0.73-2.32), number of conversions to open surgery (OR = 1.34, CI 0.76-2.37), length of hospital stays (MD = 0.12, CI 0.33-0.57), blood loss (MD = 16.73, CI 4.18-37.63) or number of rehospitalizations (OR = 0.95, CI 0.13-6.75). In terms of operative times (MD = 28.09 min, CI 11.59-44.59) and operating room times (MD = 51.39 min, CI 15.07-87.72;), the RAL technique remained inferior.

CONCLUSION

RAL does not have statistically demonstrable advantages over CL in terms of perioperative outcomes for endometriosis-related surgery.

CUSUM learning curves: what they can and can't tell us

INTRODUCTION

There has been increased interest in assessing the surgeon learning curve for new skill acquisition. While there is no consensus around the best methodology, one of the most frequently used learning curve assessments in the surgical literature is the cumulative sum curve (CUSUM) of operative time. To demonstrate the limitations of this methodology, we assessed the CUSUM of console time across cohorts of surgeons with differing case acquisition rates while varying the total number of cases used to calculate the CUSUM.

METHODS

We compared the CUSUM curves of the average console times of surgeons who completed their first 20 robotic-assisted (RAS) cases in 13, 26, 39, and 52 weeks, respectively, for their first 50 and 100 cases, respectively. This analysis was performed for prostatectomy (1094 surgeons), malignant hysterectomy (737 surgeons), and inguinal hernia (1486 surgeons).

RESULTS

In all procedures, the CUSUM curve of the cohort of surgeons who completed their first 20 procedures in 13 weeks demonstrated a lower slope than cohorts of surgeons with slower case acquisition rates. The case number at which the peak of the CUSUM curve occurs uniformly increases when the total number of cases used in generation of the CUSUM chart changes from 50 to 100 cases.

CONCLUSION

The CUSUM analyses of these three procedures suggests that surgeons with fast initial case acquisition rates have less variability in their operative times over the course of their learning curve. The peak of the CUSUM curve, which is often used in surgical learning curve literature to denote "proficiency" is predictably influenced by the total number of procedures evaluated, suggesting that defining the peak as the point at which a surgeon has overcome the learning curve is subject to routine bias. The CUSUM peak, by itself, is an insufficient measure of "conquering the learning curve."

Learning laparoscopic hysterectomy: analysis of different surgeons' individual learning curves

OBJECTIVE

The aim of this study was to examine the development of surgical skills among surgeons learning total laparoscopic hysterectomy (TLH), using differences in complication rates between surgeons with different levels of experience and analyzing the development of individual operating times.

STUDY DESIGN

This retrospective, single-center cohort study included 576 total laparoscopic hysterectomy procedures conducted between January 2015 and December 2019 at the municipal hospital in Karlsruhe, Germany. All TLHs were performed by eight surgeons, two of whom were experienced and six inexperienced. Complications were graded using the Clavien-Dindo classification.

RESULTS

No differences in complication rates were seen between experienced and inexperienced surgeons. With growing numbers of procedures, most surgeons quickly became faster, leading to reduced operating times. However, experienced surgeons who had performed more than 100 procedures also became faster, not reaching a time plateau after adjustment for weight of the uterus, presurgery score, and adnexal score.

CONCLUSIONS

Learning laparoscopic hysterectomy in routine practice is safe for patients, and surgeons rapidly become faster as growing numbers of procedures are performed. Operating times for experienced surgeons who have carried out more than 100 operations also improve, and a time plateau is not reached.