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Robot-Assisted Surgery for Endometrial Cancer Using KangDuo versus Da Vinci Systems: A Retrospective Comparative Study

Tianbo Liu, Ma Li, Wei Wang, Yue Xu, Ying Gao, Ge Yu, Jialiang Gao, Jie Chen

Year
2025
Citations
2
Access
Open access

Abstract

Background: With the advancement of medical technology, robotic-assisted surgery has emerged as a promising approach for the management of endometrial cancer (EC). This retrospective comparative study aimed to evaluate the efficacy, safety, and functional outcomes of two robotic systems-Kangduo (KD-RAS) and Da Vinci (DV-RAS)-in the treatment of EC. Methods: This study included patients with stage T1 EC who underwent robotic-assisted surgery using either the Kangduo or Da Vinci system at Harbin Medical University Cancer Hospital. A comprehensive statistical analysis was conducted on their perioperative clinical data, encompassing preoperative, intraoperative, and postoperative parameters. Results: A total of 211 patients were enrolled in this study, including 125 in the KD-RAS group and 86 in the DV-RAS group. The surgical success rate was 100% in both groups, with no significant differences observed in preoperative baseline characteristics (P > 0.05). There were also no significant differences between the two groups in terms of blood loss, transfusion requirements, or Clavien-Dindo grade I/II complications (P > 0.05). However, the KD-RAS group exhibited longer operation time, console time, time to first flatus, and length of hospital stay compared to the DV-RAS group (P < 0.05). Notably, both total hospitalization costs and surgical expenses were significantly lower in the KD-RAS group than in the DV-RAS group (P < 0.05). Conclusion: The Kangduo robotic system demonstrates comparable efficacy and equivalent safety profiles to the Da Vinci system, supporting its non-inferiority in clinical performance for the treatment of early-stage endometrial cancer.

Keywords

Endometrial cancerRetrospective cohort studyRobotGeneral surgeryComputer scienceMedicineGynecologyCancerSurgeryArtificial intelligence

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