Comparison of health-related quality of life of women undergoing robotic surgery, laparoscopic surgery or laparotomy for gynecologic conditions: A cross-sectional study

Global research hotspots and trends on robotic surgery in obstetrics and gynecology: a bibliometric analysis based on VOSviewer

Objective

Over the last two decades, the quantity of papers published in relation to robotic surgery in obstetrics and gynecology has continued to grow globally. However, no bibliometric analysis based on VOSviewer has been performed to evaluate the past and present of global research in the field. In this study, we aimed to analyze the bibliometric characteristics of papers on robotic surgery in obstetrics and gynecology to reveal research hotspots and trends in this field.

Methods

The Web of Science Core Collection was searched for scientific papers on robotic surgery in obstetrics and gynecology published between January 1, 1998 and December 31, 2023. Bibliometric metadata of each selected paper was extracted for analysis. The results were visualized by VOSviewer (version 1.6.18).

Results

A total of 1,430 papers met the inclusion criteria. The United States had the highest total link strengths and contributed the most papers (n = 793). The Mayo Clinic produced the largest number of papers (n = 85), and Professor Pedro T Ramirez contributed the most papers (n = 36). The number of citations ranged from 0 to 295 with a total sum of 29,103. The Journal of Minimally Invasive Gynecology published the most relevant papers (n = 252). Keywords were classified into six clusters based on co-occurrence data, of which cluster 1, cluster 4 and cluster 6 had more main keywords with the largest average publication year.

Conclusions

This is the first VOSviewer-based bibliometric analysis of robotic surgery research in obstetrics and gynecology. The United States was the leading country, and the Journal of Minimally Invasive Gynecology was the most productive journal in the field. Scientists and institutions from around the world should push their boundaries to bring about deep collaboration. The main research topic has always been the use of robotic surgery in the treatment of gynecologic malignancies. More randomized controlled trials need to be conducted to compare surgical outcomes of robotic surgery with other surgical approaches. Robotic sacrocolpopexy for pelvic organ prolapse has become a new research hotspot, and robotic surgery for sentinel lymph node detection in gynecologic malignancies are more potential directions for future research.

Comparison between Laparoscopic and Robotic Approach for Sentinel Lymph Node Biopsy in Endometrial Carcinoma Women

Robotic surgery has been approved as an alternative to laparoscopy to improve surgical outcomes. There is neither a consensus nor a systematic assessment of the literature about the superiority of the robotic approach over the laparoscopic one for sentinel lymph node (SLN) biopsy in endometrial carcinoma (EC) women. Therefore, a systematic review and meta-analysis was performed to compare the laparoscopic and robotic approaches for SLN biopsy in EC patients. Five electronic databases were queried from their inception to May 2022 for peer-reviewed studies, comparing such approaches in SLN biopsy in EC patients. The rate of detected SLN, dissected SLN, intraoperative and postoperative complications, conversion to laparotomy, number of dissected SLN, and SLN identification and dissection time were compared between the laparoscopic and robotic approaches for SLN biopsy in EC patients. Odds ratios with 95% confidence intervals were calculated when possible. Two studies with 660 EC women (364 who had undergone laparoscopy, and 296 who had robotic surgery) were included. No assessed outcome showed significant differences between the two approaches. In conclusion, the laparoscopic and robotic approaches for SLN biopsy in EC patients appeared to not differ, in terms of SLN detection, intraoperative and postoperative complications, conversion to laparotomy, number of dissected SLN, and SLN identification and dissection time.