Integration of a collaborative robotic platform in laparoscopic cholecystectomy: safety, feasibility, and operative time variability

Laparoscopic cholecystectomy is a high-volume procedure with relatively short operative times, leaving limited margin for further reduction in mean duration. However, variability in operative performance, compounded by anatomical variation and differing degrees of inflammation, may substantially affect operative duration and operating room efficiency. The Maestro™ Platform is a bedside, AI-powered, co-manipulated surgical assistance system designed to improve visualization, stability, and ergonomics during MIS while preserving surgeon autonomy, standard laparoscopic instrumentation, and conventional operative technique. This study aims to assess the operative and perioperative outcomes of Maestro-assisted versus conventional laparoscopic cholecystectomy, with a focus on variability in operative time. This study prospectively included 79 Maestro-assisted cholecystectomies procedures. Those cases were retrospectively compared with 79 consecutive baseline laparoscopic cholecystectomies performed by the same surgical team. Demographic data, operative time, length of stay and 30-day complications were analyzed. Statistical Process Control (SPC) charts were generated to evaluate the process stability and variability for operative times. The Maestro demonstrated a 35% reduction in operative time variability (p < 0.001). The SPC charts show significantly reduced variability and greater process stability with the Maestro Platform than conventional laparoscopy. Postoperative outcomes were comparable. No device-related complications or conversions occurred. Maestro-assisted cholecystectomy demonstrated operative time and perioperative outcomes comparable to conventional laparoscopy, while showing a significant reduction in operative time variability. For short procedures, this improved predictability may offer substantial workflow and scheduling advantages, such as more on-time starts and reduced overtime hours.