Clinical application analysis of a novel robotic system for total hysterectomy

Abstract

Objective

This study aims to explore the feasibility, safety, and clinical outcomes of a novel robotic-assisted total hysterectomy using the Endoscopic Surgical Robot MT1000 (Shanghai MicroPort Medbot CO., Ltd., Shanghai China). Additionally, it seeks to standardized surgical protocols and establish the learning curve for the surgical team performing the new robotic-assisted total hysterectomy.

Methods

A retrospective analysis was conducted on 34 cases of robotic-assisted total hysterectomy by using the Endoscopic Surgical Robot MT1000 (novel robotic group) at the Second Affiliated Hospital of Dalian Medical University from 2022 to 2024. These cases were individually compared with 35 cases of da Vinci robotic-assisted total hysterectomy (da Vinci robotic group) and 73 cases of traditional laparoscopic total hysterectomy (traditional laparoscopic group) in pairwise comparisons, all carried out by the same surgical team during the same period. Key indicators such as surgical duration, intraoperative blood loss, and time to first flatus post-surgery were observed. Additionally, the CUSUM method was employed to analyze the learning curve for the new robotic total hysterectomy.

Results

The novel robotic system demonstrated significant intraoperative and postoperative differences compared to conventional laparoscopy. Specifically, the novel robotic group exhibited higher intraoperative adhesion scores (mean difference ​= ​0.65; 95% CI [0.08, 1.21]; p ​= ​0.025), reduced intraoperative blood loss (mean difference: −20.27 ​mL; 95% CI [-31.82, −8.71]; p ​< ​0.001), and accelerated postoperative recovery evidenced by a shorter time to first flatus (mean difference: 9.37 ​h; 95% CI [-14.35, −4.39]; p ​< ​0.001), though with prolonged operative time (mean difference ​= ​20.71 ​min; 95% CI [6.34, 35.08]; p ​= ​0.05). In contrast, comparisons between the novel robotic and da Vinci systems showed no statistically significant differences across all parameters (all p ​> ​0.05). Learning curve analysis indicated that both the surgeon and the assistant reached a proficient level after completing 20 surgeries, with no significant differences in surgical metrics across various stages (p ​> ​0.05).

Conclusion

The new robotic total hysterectomy offers significant advantages in reducing intraoperative blood loss and promoting postoperative recovery, while also maintaining lower operational costs for both the facility and patients. The surgical team can rapidly master this technology, which can also be applied for remote surgeries via 5G communication, demonstrating good safety and feasibility, and warranting clinical promotion.