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Learning Curve for Single-port Robot-assisted Urological Surgery: Single-center Experience and Implications for
Antony A Pellegrino1, Francesco Pellegrino2, Donato Cannoletta1
1Division of Oncology/Unit of Urology, Urological Research Institute, IRCCS Ospedale San Raffaele, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy; University of Illinois at Chicago, Department of Urology, Chicago, IL, USA.
Background And Objective:
Understanding the learning curve for the da Vinci single-port (SP) surgical robot is crucial for adoption, training, and enhancement of surgical safety and efficiency. Our aim was to assess the impact of both overall experience (O-EXP) and procedure-specific experience (PS-EXP) on perioperative outcomes across various SP surgeries.
Methods:
We analyzed data for 387 consecutive SP surgeries conducted by a high-volume surgeon from December 2018 to July 2023. These included SP robot-assisted radical prostatectomy (SP-RARP), robot-assisted simple prostatectomy (SP-RASP), and robot-assisted nephrectomy (SP-RANP). We used multivariable logistic regression to evaluate the relationship between surgeon experience and outcomes, and locally weighted scatterplot smoothing analysis to graphically explore the risk of postoperative complications according to O-EXP.
Key Findings And Limitations:
The 387 SP procedures assessed included 172 (44%) SP-RARP, 53 (14%) SP-RASP, and 162 (42%) SP-RANP cases. Overall, 17% of patients had a complication of any grade, 6% experienced severe complications (Clavien-Dindo grade ≥3), and 8% required readmission. Both O-EXP and PS-EXP were associated with a lower risk of complications. The odds ratios for the incidence of complications per increment of 10 procedures were 0.83 (95% confidence interval [CI] 0.76-0.89) for PS-EXP and 0.93 (95% CI 0.90-0.96) for O-EXP. PS-EXP was also associated with a shorter operative time (β = -3.9, 95% CI -4.9 to -2.9). The risk of complications reached a minimum at 30 SP-RASP, 70 SP-RANP, and 150 SP-RARP cases. Our study is limited by its retrospective design, single-surgeon experience, and lack of functional outcome assessment.
Conclusions And Clinical Implications:
Robot-assisted surgery with the da Vinci SP robot has a distinctive learning curve that is influenced by the platform and procedure-specific characteristics. For surgeons new to SP surgery, RASP and renal procedures had the earliest learning curve success and should be approached first, with RARP attempted only when the surgeon has become accustomed to the SP platform.
Patient Summary:
We investigated the learning curve for a surgical robot that uses just one keyhole incision. We found that the time to reach proficiency for urological surgeries with this specific robot, measured as the rate of complications, is faster for some procedures than for more complex operations. This information can help in improving surgeon training and patient safety.
