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Updated: Aug 5, 2025

Robotics in Surgery: A Modular Robotic Platform Driven Gastric Wedge Resection
Published on: February 7, 2025
The comparison of short-term outcomes between robotic and laparoscopic radical distal gastrectomy
Yang Song1, Qianshi Zhang1, Zhen Feng1
1Department of General Surgery, The Second Hospital of Dalian Medical University, Dalian, 116023, China.
Purpose:
The study's objectives were to compare the short-term outcomes of robotic radical distal gastrectomy (RDG) with laparoscopic radical distal gastrectomy (LDG) for patients with gastric cancer and investigate the learning curve of RDG.
Methods:
The cumulative sum (CUSUM) method was used to retrospectively analyze consecutive gastric cancer patients undergoing RDG between January 2019 and October 2021. The duration of surgery, clinical-pathological characteristics, and short-term outcomes were evaluated according to the two phases of the learning curve (learning period versus mastery period). We also compared the clinical-pathological characteristics and short-term outcomes between cases in the mastery period and LDG.
Results:
Data from 290 patients were included in this analysis, 135 RDG and 155 LDG cases. The learning period was 20 cases. There were no significant differences in clinical-pathological characteristics between the learning period and mastery period. Compared with the learning period, the mastery period had a significant reduction in total operation time, docking time, pure operation time, and estimated blood loss, and a significant increase in hospital costs (P=0.000, 0.000, 0.000, 0.003, and 0.026, respectively). Compared with LDG, robotic cases in mastery period had a longer operative time, shorter first postoperative flatus time, and more hospital costs (P=0.000, 0.005, and 0.000, respectively).
Conclusions:
RGD may fasten to recover gastrointestinal function faster after the operation, can be mastered easily after a reasonable number of cases, and was associated with safe and satisfactory short-term outcomes before and after the learning curve.

