ArticleJournal of robotic surgery2021
An analysis of operating time over the years for robotic-assisted surgery in gynecology and gynecologic oncology.
Article in Journal of robotic surgery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
9 citing papers in PubMed, 14 citations in OpenAlex.
- Advancing paediatric robotic surgery: building the foundation with databases.Journal of robotic surgery · 2026Article
- Robotic gynecologic surgery in Saudi Arabia: a descriptive retrospective cohort study of contemporary second-decade perioperative outcomes.BMC women's health · 2026Article
- The dexter robotic system in gynecological surgery: preliminary clinical data from routine use.Journal of robotic surgery · 2026Article
- Learning curves, safety, and experiences of a tertiary surgical center in the introduction of robotic-assisted surgery in gynecologic oncology.Archives of gynecology and obstetrics · 2026Article
- Introduction of Robot-assisted Surgery for Benign Total Hysterectomy with Salpingectomy: Learning Curve, Safety and Experience in a Tertiary Surgical Center.Geburtshilfe und Frauenheilkunde · 2025Article
- Surgical efficiency for gynecological surgery with a single robotic console: the value of the surgical team and robotic technology in maximizing efficiency on intensive surgical days: a comprehensive analysis.Journal of robotic surgery · 2025Article
- Proficiency-based progression training in robot-assisted laparoscopy for endometrial cancer: peri-operative and survival outcomes from an observational cohort study.Frontiers in medicine · 2024Article
- Robot-Assisted Surgery in Gynecology.Cureus · 2022Review
- Global trends and hotspots in research of robotic surgery in oncology: A bibliometric and visual analysis from 2002 to 2021.Frontiers in oncology · 2022Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Robotic-assisted surgery has a shorter learning curve enabling the surgeons to do complex surgeries in a minimally invasive way. This study analyzed how the time taken for robotic-assisted procedures in gynecology and gynecologic oncology has changed over the years in a university teaching institution. Details were taken from a prospectively maintained electronic database after obtaining permission from the hospital ethics committee. All patients who underwent robotic surgery for gynecologic problems at this center from February 2015 till December 2019 were included. The clinical, perioperative, postoperative and pathologic details were collected from the prospectively maintained database. To analyze quantitative data, student t test was used. Chi-square test was performed to compare categorical variables. 655 patients underwent robotic-assisted surgery during this period. The majority of the patients underwent surgery for uterine cancer (49%). There was a significant improvement in total surgical time (250 vs. 165 min), docking time (12.6 vs 8.9 min), and console time (130 vs. 95 min) between the first and second year (2015-16). The next 2 years (2017 and 18) did not show a significant decrease in the total surgery time and console time, but docking times improved in 2017 (5.5 vs 8.5 min) compared to 2016. In 2019, there was a significant improvement in all surgical times compared to previous years. This study shows that robotic surgery has a lot of scope for improvement in surgical performance beyond its first and second years. The surgical performance as seen from the improved surgical times keeps on improving even after many years.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.