To investigate the learning curve characteristics, influencing factors, and optimization strategies of domestic single-port robotic assisted gynecological surgery, and to analyze proficiency inflection points under different surgical procedures and surgeon backgrounds.

A prospective, multicenter, single-arm clinical trial was conducted at six hospitals across China between Jan. 2023 and Oct. 2025. A total of 97 patients undergoing robotic assisted gynecological surgery using the Shurui SR-ENS-600 system were enrolled, including 32 cases of ovarian cystectomy, 11 cases of myomectomy, 45 cases of hysterectomy, and 9 cases of endometrial cancer staging. Docking time was recorded and compared with literature data. The cumulative sum (CUSUM) method was used to analyze the trend of console time and to identify proficiency inflection points.

In this study, the median age of patients undergoing endometrial cancer staging was lower than that reported in the literature (45 years vs. 61 years), while the age of myomectomy group was higher (42.27 years vs. 36.98 years). The learning curve for docking time was short, with median docking times ranging from 3.00 to 6.00 minutes across hospitals, and 80.4% of cases completed docking within 5 minutes. Significant inter-hospital differences in the learning curves of console time were observed: hospital 1 exhibited a "decline-rebound-decline" pattern, entering the proficiency phase after approximately 25 cases; hospital 5 achieved proficiency from the first case but showed limited subsequent improvement; hospital 6 demonstrated the most typical learning curve, reaching a stable plateau at 5-6 cases. Significant heterogeneity in learning curve inflection points was also found across different surgical procedures: routine procedures (Type 1) achieved proficiency quickly, while difficult procedures (Type 3) required 22 cases to reach a stable plateau (median console time of 105 minutes).

The learning curve for domestic single-port robotic gynecological surgery exhibits significant procedure-dependency and inter-individual heterogeneity. Difficult procedures require more than 20 cases to achieve proficiency, while routine procedures can reach a stable level within 5 cases. Surgeons′ prior experience in single-port laparoscopy and multi-port robotic surgery can significantly shorten the learning cycle for single-port robotic surgery. The domestic Shurui SR-ENS-600 system demonstrates comparable docking time and operative time to the da Vinci SP system, indicating good clinical accessibility and potential for widespread adoption. Dual-console teaching and augmented reality-assisted feedback techniques can help optimize the learning curve.