Quantifying the Learning Curve in Robotic Peritoneal Flap Vaginoplasty
Kshipra Hemal1, Gaines Blasdel2, Augustus Parker1
1From the Hansjörg Wyss Department of Plastic Surgery, New York University Langone Health, New York, NY.
Annals of Plastic Surgery
|April 1, 2025
Summary
The learning curve for robotic-assisted peritoneal flap gender-affirming vaginoplasty (RPGAV) is 300 cases. Outcomes like shorter hospital stays and fewer revisions improve with surgeon experience.
Area of Science:
- Robotic Surgery
- Gender-Affirming Care
- Surgical Education
Background:
- The learning curve (LC) quantifies the mastery of new surgical techniques.
- Robotic-assisted peritoneal flap gender-affirming vaginoplasty (RPGAV) is an evolving procedure.
- Assessing the LC for RPGAV is crucial for optimizing surgical training and patient outcomes.
Purpose of the Study:
- To evaluate the learning curve for robotic-assisted peritoneal flap gender-affirming vaginoplasty (RPGAV).
- To identify factors influencing operative time (OT) during RPGAV.
- To compare outcomes between the learning and expert phases of RPGAV.
Main Methods:
- Retrospective chart review of 500 consecutive RPGAV cases (09/2017-02/2023).
- Analysis of operative times (OT) to determine the learning curve plateau.
- Comparison of perioperative and postoperative outcomes between early and late phases of the learning curve.
Main Results:
- The learning curve for RPGAV was determined to be 300 cases, after which operative times stabilized.
- Increased body mass index significantly increased OT, while single-port robotic systems decreased OT.
- The expert phase (last 200 cases) demonstrated reduced length of stay, fewer blood transfusions, and lower rates of revision surgery compared to the learning phase (first 300 cases).
Conclusions:
- A cohort of 300 cases is required to achieve proficiency in robotic-assisted peritoneal flap gender-affirming vaginoplasty.
- Patient BMI and robotic system type (single-port vs. multiport) are significant determinants of operative time.
- Surgical experience in RPGAV leads to demonstrable improvements in clinical efficiency and patient outcomes.


